Visualization method, system, medium and equipment for real-time plant bio-electricity signal and static data

Abstract

The invention relates to a real-time plant bioelectricity signal and static data visualization method and system, a medium and equipment. The method comprises the steps that real-time plant electric signal data per second and static plant soil humidity data per hour are collected; performing data type conversion and mapping on the real-time resistance data per second of the plant and the static soil humidity data per hour of the plant to obtain volume and pitch, and forming music by the volume and the pitch; analyzing an audio signal in the music, and extracting a volume value in the audio signal to adjust the motion amplitude of the visual model so as to realize sound-picture interaction; and finally, carrying out effect scoring on sound and picture interaction. According to the invention, the bioelectricity signals and static data of plants are converted into artistic and interactive music and visual art visual display in real time. The visual effect of the plant bio-electricity signals is achieved through data processing and mapping, and a brand-new art expression mode is provided through the sound and picture synchronization technology.

Description

Technical Field

[0001] The present invention belongs to the technical field of visualization and multimedia art, and particularly relates to a method, system, medium and device for visualizing real-time plant bioelectric signals and static data. Background Art

[0002] Visualization is a theory, method and technology that uses computer graphics and image processing technologies to convert data into graphics or images for display on a screen and perform interactive processing.

[0003] Plants have the ability to sense and respond to the environment. Plants have evolved to sense and respond to environmental stimuli by generating and transmitting bio-signals within living cells. Scholars at home and abroad have also carried out relevant research in different directions on plant electric signals. Bioelectric phenomena refer to the phenomena in which voltages are generated and voltages change in the organs, tissues and cells of organisms during their life activities. However, most of the relevant domestic research focuses on collecting and analyzing plant electric signals and applying them to guide the development of smart agriculture as training data, and no research on their artistic visualization has been carried out. For example, Cui Xudong analyzed and studied plant electric signals based on LabVIEW and BP neural network, explored the relationship between electric signals and growth environment, and established a corresponding model to achieve unmanned, automated and intelligent agricultural planting.

[0004] With the increasing diversification of the application of visualization technology in the field of art design, it is a direction worth exploring to utilize new media interaction technology as a means of expression based on data thinking. In the interdisciplinary field of art and technology, converting biological signals into artistic visualizations is an emerging exploration direction. The discovery of bioelectric signals in plants also provides opportunities for designs related to plant biology. YOUYANG HU et al. proposed to analyze plant biological signals by applying machine learning algorithms and convert the responses of plants to environmental stimuli into visual and acoustic expressions, namely a method for controlling sound lighting devices to generate variable cymatics patterns. The team developed a bioamplifier, trained a model for analyzing and processing bioelectric signals, and input the analysis results into a pure data patch, which generates corresponding sounds to a resonant speaker. The speaker vibrates the water in a petri dish to produce various resonant waveforms. The above work undoubtedly provides guiding work for the amplification, analysis, and artistic visualization of plant bioelectric signals. However, in terms of the mapping dimension of data, it only uses the mapping of plant bioelectric signals to sound frequency, i.e., the volume dimension, and uses it to vibrate the water surface to produce visual effects in the physical world. Based on the deficiencies in the above research fields at home and abroad, the author cross-designed multiple disciplines including design, computer science, plant biology, and musicology, and proposed an audio-visual interaction visualization method based on static data and dynamic real-time plant bioelectric data, mapping static data to musical pitch, mapping dynamic real-time plant bioelectric data to volume, and further mapping it to the amplitude of a computer vision image.

[0005] Existing technologies mostly rely on the visualization of static data and lack real-time feedback and interaction for dynamic real-time data. Traditional visualization methods for bioelectric signals are usually limited to static images or single audio outputs, lacking real-time performance and interactivity. Moreover, existing research related to plant bioelectric signals mostly focuses on the field of smart agriculture, with relatively few studies in the direction of artistic visualization. And in the research on the artistic visualization of plant bioelectricity, the mapping dimension of data is single. Summary of the Invention

[0006] In order to overcome the problems existing in the prior art, the present invention provides a visualization method, system, medium, and device for real-time plant bioelectric signals and static data to overcome the current defects.

[0007] A visualization method for real-time plant bioelectric signals and static data, the method comprising:

[0008] S1. Collect real-time plant electrical signal data per second and static plant soil humidity data per hour;

[0009] S2. Perform data type conversion and mapping on the real-time plant resistance data per second and the static plant soil humidity data per hour to obtain volume and pitch, and the volume and pitch form music;

[0010] S3. Analyze the audio signal in the music, extract the volume value therein to adjust the motion amplitude of the visual model, and achieve audio-visual interaction;

[0011] S4. Score the effect of the audio-visual interaction.

[0012] For the aspects and any possible implementation manners as described above, a further implementation manner is provided, wherein the bioelectric signal includes a plant current signal or a plant resistance signal.

[0013] For the aspects and any possible implementation manners as described above, a further implementation manner is provided, wherein the plant is a herbaceous plant or a woody plant.

[0014] For the aspects and any possible implementation manners as described above, a further implementation manner is provided, wherein the sliding window method is used to process the plant electric signal data, sample all the plant resistance signal values obtained within the window, and calculate the standard deviation and the coefficient of variation.

[0015] For the aspects and any possible implementation manners as described above, a further implementation manner is provided, wherein the coefficient of variation of the static data and the coefficient of variation of the plant electric signal data are both greater than 0.05.

[0016] For the aspects and any possible implementation manners as described above, a further implementation manner is provided, wherein in S2, the volume is also analyzed, and the RMS Power index is used to detect the generated volume size, where 0 represents complete silence and 1 represents the maximum volume.

[0017] For the aspects and any possible implementation manners as described above, a further implementation manner is provided, wherein S4 specifically includes using the standard deviation, the coefficient of variation, and the set audio-visual synchronization scoring parameters to evaluate the audio-visual synchronization effect.

[0018] The present invention also provides an audio-visual synchronization visualization system based on real-time plant bioelectric signal data and static data, which is used to implement the method described above and includes:

[0019] An acquisition module, which is used to acquire real-time plant electric signal data per second and static plant soil humidity data per hour;

[0020] A conversion and mapping module, which is used to perform data type conversion and mapping on the real-time plant resistance data per second and the static plant soil humidity data per hour to obtain the volume and pitch, and the volume and pitch form music;

[0021] An interaction module, which is used to analyze the audio signal in the music, extract the volume value therein to adjust the motion amplitude of the visual model, and achieve audio-visual interaction;

[0022] A scoring module for scoring the effect of audio-visual interaction.

[0023] The present invention provides a computer-readable storage medium storing a program which, when executed by a processor, implements the method described above.

[0024] The present invention provides an electronic device comprising a processor and a memory for storing a program executable by the processor, and when the processor executes the program stored in the memory, the method described above is implemented.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The method of the present invention first collects real-time plant electrical signal data per second and static plant soil humidity data per hour; performs data type conversion and mapping on the real-time plant resistance data per second and the static plant soil humidity data per hour to obtain volume and pitch, and the volume and pitch form music; analyzes the audio signal in the music, extracts the volume value therein to adjust the motion amplitude of the visual model, and realizes audio-visual interaction; finally, scores the effect of the audio-visual interaction. The beneficial effects of the present invention are as follows: Based on the bioelectrical signals and static data of plants, they are real-time converted into artistic and interactive music and visual art visual displays. Through data processing and mapping, the visualization effect of plant bioelectrical signals is completed, and through audio-visual synchronization technology, a new art expression method is provided. It enriches the expression forms of multimedia art, and also brings an immersive experience to the audience, establishing an intuitive and emotional connection between the biological activities of plants and human art creation. In addition, the application of the present invention may also promote interdisciplinary research, such as the integration of fields such as botany, musicology, visual art, and human-computer interaction, providing new possibilities for future art creation and scientific research. Description of the Drawings

[0027] Figure 1 It is a schematic flowchart of the method of the present invention. Detailed Embodiments

[0028] To better understand the technical solution of the present invention, the content of the present invention includes but is not limited to the following detailed embodiments, and similar technologies and methods should be regarded as within the scope of protection of the present invention. To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the drawings and specific embodiments.

[0029] It should be clear that the embodiments described in the present invention are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0030] A visualization method for real-time plant resistance bioelectric data and static herbaceous plant soil humidity data provided by the present invention, the method comprising:

[0031] S1. Collect real-time plant electrical signal data per second and static plant soil humidity data per hour;

[0032] S2. Perform data type conversion and mapping on the real-time plant resistance data per second and the static plant soil humidity data per hour to obtain volume and pitch, and the volume and pitch form music;

[0033] S3. Analyze the audio signal in the music, extract the volume value therein to adjust the motion amplitude of the visual model, and realize audio-visual interaction;

[0034] S4. Score the effect of the audio-visual interaction.

[0035] Specifically, the process of the present invention is as follows: The input data of the present invention is real-time plant resistance data per second and historical static plant soil humidity data per hour, and the output is music generated based on the real-time bioresistance data and static soil humidity data, and the computer vision art modeling scene effect according to the change of the music volume. The steps of the present invention are:

[0036] a. Data collection

[0037] (1) Collection of real-time plant resistance data per second.

[0038] Plant bioelectric signals include plant current signals or plant resistance signal values, etc. The herbaceous plant resistance signal value, that is, the herbaceous plant resistance value, is collected in the present invention. Collecting plant bioelectric signals includes selecting and processing plant materials, measuring, reading, and data sending. Plants include herbaceous plants and woody plants. Among them, the change of the resistance value of herbaceous plants is more obvious than that of woody plants. Therefore, herbaceous plants are preferably selected in the present invention. Measuring the plant resistance value is realized by electrodes. Electrodes and sensors are used to collect plant bioelectric signals of herbaceous plants growing in the soil. One end of the electrode is inserted or clamped on the plant leaf, and the other end is connected to the component for transmitting data and sends signals between different software and devices through serial communication. Other methods can also be used as long as plant bioelectric signals can be obtained. This measurement method is a commonly used method in the prior art and will not be elaborated in the present invention.

[0039] The resistance value of herbaceous plants is dynamically affected by environmental factors (such as temperature, humidity, light, human touch) and internal activities (such as transpiration, ion transport), showing real-time changes. Under normal circumstances, the fluctuation amplitude of the resistance value per second is small, usually in the range of ± several ohms to dozens of ohms; if subjected to strong light, touch and other severe stimuli or human interference (such as human touch), the change amplitude may reach hundreds of ohms or even more than thousands of ohms.

[0040] In the present invention, the sliding window method is used to process the real-time resistance value data of the selected herbaceous plants. The purpose is to dynamically monitor and statistically analyze the fluctuations of the real-time resistance value, and calculate the standard deviation representing the degree of dispersion of the resistance value data and the coefficient of variation representing the relative fluctuation amplitude in real time, so as to evaluate the stability and responsiveness of the resistance signal and provide a reliable basis for volume mapping. The sliding window method can continuously evaluate the data characteristics within a fixed-size window in the data stream. In the specific implementation, the parameters of the sliding window are defined as a set containing 20 consecutive data points, and each data point is a real-time resistance value of a plant collected within 1 second. The sliding window is updated over time. When a new data point enters the window, the oldest data point is removed to keep the window size constant at 20 data points. This dynamic update strategy ensures the continuity and timeliness of the analysis and can reflect the short-term fluctuation characteristics of the resistance value in real time. In the present invention, the sliding window method is used to monitor the dynamic changes of the plant resistance value in real time, calculate the standard deviation and the coefficient of variation to evaluate the volatility of the resistance signal, and ensure the dynamic expressiveness of the volume mapping.

[0041] The calculation formula for the standard deviation is:

[0042] The calculation formula for the coefficient of variation is:

[0043] where σ is the standard deviation, x i is the data value of the i-th point in the window, is the average value of the data, and N is the number of data points, which is taken as 20 in the present invention. Finally, the data results obtained by the sliding window method include the resistance value within the window and its standard deviation and coefficient of variation. These two indicators, the standard deviation and the coefficient of variation, are respectively used to judge the degree of dispersion and the fluctuation amplitude of the data.

[0044] In the present invention, when the variation is lower than or equal to 0.05, the window data is too small. If the coefficient of variation is too small, it means that the resistance signal fluctuation is insufficient. Then, it is necessary to replace the plant, sensor or use a bioelectric amplifier to amplify the signal to ensure that the mapping result of the resistance signal (i.e., the volume change) is intuitive, clear and has dynamic expressiveness. Therefore, in the present invention, the window data with a coefficient of variation above 0.05 is adopted to ensure that the subsequent generated pitch has a certain dynamic range.

[0045] (2) Collection of historical hourly static plant soil moisture data.

[0046] Soil moisture is related to the bioelectric signal of plant roots. When the humidity increases, the conductivity of the roots enhances, resulting in a decrease in the plant's resistance value; when the humidity decreases, the conductivity weakens and the resistance value increases. Therefore, the present invention utilizes the correlation and complementary strengths between the two types of data, namely resistance value and humidity, selects real-time plant resistance data and static plant soil moisture data, and maps the plant resistance data and static plant soil moisture data to generate the volume and pitch of music respectively. Since soil moisture usually changes slowly on an hourly time scale and does not fluctuate violently every second, in the present invention, the static plant soil moisture data selected during the collection period does not water the plants to avoid a sudden increase in data values and drastic changes. The data is specifically a set of fixed data measured and sorted hourly, with a fixed finite number (such as 24), and is cyclically read every second to ensure that the pitch and volume mapped by the two types of data are synchronized when generating music. The coefficient of variation of the static plant soil moisture data is also greater than 0.05, ensuring that the static plant soil moisture data has a certain degree of volatility, thereby enabling the mapped music pitch to have a certain degree of volatility.

[0047] b. Music generation

[0048] Music generation in the present invention includes data type conversion, data range adjustment, and data mapping to pitch and volume, specifically including the following steps:

[0049] (1) Data type conversion

[0050] The data types of the real-time plant bioresistance value data and the static plant soil moisture data need to be adjusted to be consistent with the pitch and volume data input types (usually integer types) that the music generation component can read. For example, if the data type of the collected plant bioelectric data is the ASCII string data type, while the pitch and volume data input types that the music generation component can read are integer types, then the data type processing from the ASCII string data type to the integer type needs to be completed. One method is to use the itoa function to convert it to UTF-encoded symbols, but at this time it is still a string, and then use the fromsymbol function to convert the string into an integer of Arabic numerals. The data of the plant bioresistance value after completing the data type conversion is V music1 , the itoa function and the fromsymbol function are commonly used conversion functions, and the present invention will not elaborate on the specific conversion process. Using the same method, the static plant soil moisture data is subjected to data type conversion, and the converted data obtained is P music1 .

[0051] (2) Data range adjustment

[0052] In the process of generating music, pitch and volume are the core dimensions. In addition, there are other dimensions that can be used for richer musical expressions, such as timbre and rhythm. In this invention, music is mainly generated using pitch and volume, and the timbre of the built-in piano in the music generation component is selected for the timbre.

[0053] In the MIDI signal of the music generation component, the ranges of pitch and volume are 0 - 127. Therefore, the real-time bioelectric data and static soil humidity data after completing data type conversion need to be constrained within the data range that the music generation component can read, that is, the numerical value of the data does not exceed its limit value to prevent normalization and affect the accuracy of the effect.

[0054] Since the plant bioresistance data ultimately needs to be mapped to the volume of music, it is necessary to match the plant bioresistance data with the MIDI data range that the music generation component can read. Considering the actual situation, multiply V music1 by a certain coefficient to adjust the value to a suitable interval and complete the equal-proportion scaling of the data to a suitable interval. That is, for V music1 perform data range adjustment to the interval of 0 - 127, and the adjusted data is V music* .

[0055] Since the static soil humidity data ultimately needs to be mapped to the pitch of music, it is necessary to match the static soil humidity data with the MIDI data range that the music generation component can read. Considering the actual situation, multiply P music1 by a certain coefficient to adjust the value to a suitable interval and complete the equal-proportion scaling of the data to a suitable interval for listening perception. Denote the adjusted P music1 after performing data range adjustment as P music* .

[0056] (3) Mapping data to pitch and volume

[0057] Input P music* and V music* into the components in the music generation software respectively. The processed static plant soil humidity data, that is, P music* is connected to the port or component that controls the pitch of music, and the processed static plant soil humidity data value is mapped to the pitch value. The processed resistance value of the plant that changes in real time, that is, V music*Connect to the port or component that controls the music volume, map the processed real-time plant bioelectrical resistance value to a volume value. After completing the above mapping, finally generate and output the music composed of pitch and volume in real time. The music generated by the present invention has dynamic real-time responsiveness through the real-time mapping of plant bioelectrical signals and soil humidity data, directly reflecting the real-time state changes of plants. The change in volume directly corresponds to the real-time dynamic fluctuation of plant bioelectrical signals, and the change in pitch corresponds to the change in soil humidity, making the music generation process reflect the integration of nature and technology. Compared with traditional music, the music of the present invention is driven by natural data, that is, its pitch and volume are not artificially created, but an artistic expression derived from the natural state of plants, enabling the imperceptible natural signals to be visualized. The generated music not only reflects the real-time changes in the plant state, but also enhances the immersive experience through the combination with the visual model, highlighting the innovation of data-driven art.

[0058] c. Analysis of music volume

[0059] In the present invention, the volume reflects the real-time dynamic changes of plant bioelectrical signals and is the main driving force for the interactive effect. The pitch is mapped from static soil humidity data, which itself changes relatively slowly and stably. To ensure the real-time and interactive nature of the audio-visual effect, no further processing is performed on the pitch, and only the volume is analyzed.

[0060] According to the MIDI (Musical Instrument Digital Interface) standard, the volume value is defined as 128 possible values (from 0 to 127). "RMS Power" refers to the root mean square power of the audio signal, which is an indicator to measure the strength of the audio signal. The value of "RMS Power" is usually between 0 and 1, where 0 means no signal (completely silent), and 1 means the signal reaches the maximum possible amplitude, that is, full scale. The present invention uses it to detect the volume of the generated music and represents it with the value of "RMSPower".

[0061] V music* and V music2 The relationship between them is expressed by the following formula:

[0062] V music2 = f(V music* )(3)

[0063] where V music2 is the volume value obtained by measuring the strength of the audio signal with "RMS Power", and the numerical range is 0 - 1. V music* is the volume value measured according to the MIDI standard, and the numerical range is 0 - 127. Establish the relationship between V music* and V music2The relationship is that since there is no module in the visual model software to directly measure the audio signal using the MIDI standard, the MIDI volume needs to be processed through the audio signal measured by, for example, RMS Power and then undergo a mapping conversion later.

[0064] Based on the above analysis of the data range of MIDI note velocity and the value range of "RMS Power", in the present invention, the value of the mapping relationship formula f between V music* and V music2 is At this time, the relationship formula is That is, the relationship between V music* and V music2 is a linear relationship.

[0065] d. Audio-visual interaction design

[0066] In the software containing the visual model, the music generated in real time in step b above is transmitted through the OSC protocol or by using the "audio file in" and "audio file out" components. The V obtained by analyzing the "RMS Power" is input to the motion amplitude parameter of the visual model, and the continuously changing V music2 is linked to the motion amplitude of the visual model, so that the continuously changing V music2 controls the visual model to move with a changing amplitude, thus completing audio-visual synchronization. When inputting a changing amplitude to the visual model, if the amplitude value is too large, it may cause the picture to distort and produce a bad visual experience. Therefore, before transmitting V music2 to the amplitude of the visual model, it is necessary to adjust the data range of V music2 , scale the value of V music2 to a certain extent, and then transmit it. music2

[0067] The relationship between the model amplitude value and the analyzed volume value V music2 is as follows:

[0068] A visual = f * V music2 (4)

[0069] A visual and V music2 are in a linear relationship, and the value of f depends on the specific situation.

[0070] e. Effect scoring of the audio-visual effect in step d above

[0071] Transmitting the real-time music through the OSC protocol or by using the "audio file in" and "audio file out" components may cause audio-visual synchronization delay. The reasons include network transmission delay, audio buffer settings, too low frame rate, or time-consuming visual effect calculation.

[0072] The audio-visual synchronization effect score is expressed by formula (5), specifically as follows:

[0073]

[0074] Among them, w is a coefficient, which is specified to take a constant value of 100 in the present invention; σ is the standard deviation, obtained from the aforementioned formula (1), is the average value of the data, is the coefficient of variation, and are obtained from the aforementioned formula (2). E sync is a parameter characterizing the audio-visual synchronization effect, and its value is specified to be equal to the number of seconds of audio-visual synchronization delay. In the present invention, the value of "the number of seconds of audio-visual synchronization delay" is set to be equal to the absolute value of the time difference between "audio trigger" and "visual effect output". The CHOP component or other components are used to record the time of audio trigger and visual effect output, and the "number of seconds of audio-visual synchronization delay" is calculated through the time difference between the two to achieve precise synchronization effect. The recording method of the above CHOP component or other components is a mature existing technology, and the present invention will not elaborate.

[0075] In the present invention, is the coefficient of variation obtained by analyzing the dynamic real-time plant bioelectric data through the sliding window method, which measures the fluctuation of the plant bioelectric data affecting the music volume dimension. E sync is a parameter characterizing the audio-visual synchronization score. Therefore, the effect score measures the audio-visual synchronization effect and the volume of the music.

[0076] Combining the characteristics of the coefficient of variation and the characteristics of the number of delay seconds, in the present invention, it is specified to select the coefficient of variation data between 0.05 and 1, and select the parameter E of the audio-visual synchronization effect sync data within 0 to 1 second. The approximate value range (related to the number of decimal places taken) of the effect score within the range and the corresponding evaluation criteria are as follows:

[0077] (1) 0 ≤ E sync ≤ 0.2 5 ≤ E error <51.6

[0078] (2) 0.2 < E sync ≤ 1 51.6 < E error ≤ 250

[0079] (3) 0 ≤ E sync ≤ 0.2 50 ≤ E error ≤ 102

[0080] (4) 0.2 < E sync ≤121 < E error ≤2500

[0081] In case (1), the fluctuation of the plant bioelectric data and the audio-visual synchronization effect are both relatively good. Therefore, 5 ≤ E error <51.6 is a scoring range with relatively good effects. It can be considered that the effects are relatively good when the score is around 5 - 51.6.

[0082] In case (2), the fluctuation of the plant bioelectric data is relatively large, and the audio-visual synchronization delay is relatively obvious.

[0083] In case (3), the fluctuation of the plant bioelectric data is relatively large, and the audio-visual synchronization delay is relatively small.

[0084] In case (4), the fluctuation of the plant bioelectric data is relatively small, and the audio-visual synchronization delay is relatively obvious.

[0085] Except for case (1), in other cases, the value ranges do not overlap with that of case (1). In cases (3) and (4), although the value ranges partially overlap with that of case (1), and E sync are both in relatively appropriate ranges. In summary, it can be considered that when 5 ≤ E error <51.6, the comprehensive visualization effect of the music and visual dimensions is relatively good.

[0086] As an embodiment disclosed in the present invention, the present invention also provides an audio-visual synchronization visualization system based on real-time plant bioelectric signal data and static data. The system is used to implement the method, including:

[0087] An acquisition module, configured to acquire real-time plant electric signal data per second and static plant soil humidity data per hour;

[0088] A conversion and mapping module, configured to perform data type conversion and mapping on the real-time plant resistance data per second and the static plant soil humidity data per hour to obtain volume and pitch, and the volume and pitch form music;

[0089] An interaction module, configured to analyze the audio signal in the music, extract the volume value therein to adjust the motion amplitude of the visual model, and implement audio-visual interaction;

[0090] A scoring module, configured to score the effect of the audio-visual interaction.

[0091] As an embodiment disclosed in the present invention, the present invention also provides a computer-readable storage medium storing a program, which when executed by a processor, implements the method.

[0092] As an embodiment disclosed by the present invention, the present invention further provides an electronic device, including a processor and a memory for storing a program executable by the processor. When the processor executes the program stored in the memory, the method described above is implemented.

[0093] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms of "a", "the" and "said" used in the embodiments of the present invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0094] The above description shows and describes several preferred embodiments of the present invention. However, as mentioned above, it should be understood that the present invention is not limited to the form disclosed herein, should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be changed within the scope of the application concept described herein through the above teachings or the technology or knowledge in the relevant field. Any changes and variations made by those skilled in the art without departing from the spirit and scope of the present invention shall fall within the protection scope of the appended claims of the present invention.

Claims

1. A method for visualizing real-time plant bioelectric signals and static data, characterized in that: The method comprises: S1. Collect real-time plant electrical signal data per second and static plant soil moisture data per hour; S2. The real-time plant resistance data per second and the static plant soil moisture data per hour are converted and mapped to obtain volume and pitch, which constitute music; S3. Analyze the audio signal in the music and extract the volume value to adjust the motion amplitude of the visual model to achieve audio-visual interaction; S4. Score the effectiveness of audio-visual interaction.

2. The method according to claim 1, characterized in that Bioelectric signals include plant current signals or plant resistance signals.

3. The method according to claim 1, characterized in that The plant is a herbaceous plant or a woody plant.

4. The method according to claim 2, characterized in that: The plant electrical signal data is processed using a sliding window method, all plant resistance signal values ​​obtained within the window are sampled, and the standard deviation and coefficient of variation are calculated.

5. The method according to claim 4, characterized in that The coefficient of variation of the static data and the coefficient of variation of the plant electrical signal data are both greater than 0.

05.

6. The method according to claim 1, characterized in that S2 also includes volume analysis, using the RMSPower indicator to detect the volume generated, 0 means complete silence, and 1 means the maximum volume.

7. The method according to claim 4, characterized in that S4 specifically includes using standard deviation, coefficient of variation and set audio-visual synchronization scoring parameters to evaluate the audio-visual synchronization effect.

8. A sound and picture synchronization visualization system based on real-time plant bioelectric signal data and static data, characterized in that: The system is used to implement the method according to any one of claims 1 to 7, comprising: The acquisition module is used to collect real-time plant electrical signal data per second and static plant soil moisture data per hour; A conversion and mapping module, used for performing data type conversion and mapping on the real-time plant resistance data per second and the static plant soil moisture data per hour to obtain volume and pitch, wherein the volume and pitch constitute music; The interactive module is used to analyze the audio signal in the music and extract the volume value to adjust the motion amplitude of the visual model to achieve audio-visual interaction; The scoring module is used to score the effect of audio and video interaction.

9. A computer-readable storage medium storing a program, characterized in that: When the program is executed by a processor, the method described in any one of claims 1 to 7 is implemented.

10. An electronic device comprising a processor and a memory for storing a program executable by the processor, characterized in that: When the processor executes the program stored in the memory, the method described in any one of claims 1 to 7 is implemented.

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