Operation monitoring method and device for ecological cabin

Abstract

The invention relates to the field of ecological cabins, and discloses an operation monitoring method and device of an ecological cabin, and the method comprises the steps: in the operation process of the ecological cabin, based on a preset sensor array, collecting environmental parameters in the ecological cabin, the environmental parameters including temperature, humidity, illumination intensity and CO2 concentration; based on the collected environmental parameters, growth parameters of the ecological cabin are calculated, and the growth parameters comprise photosynthesis efficiency PE and water utilization efficiency WUE; according to the collected environment parameters and growth parameters, the growth index GI of plants in the ecological cabin is calculated; according to the calculated plant growth index GI, adjusting environmental parameters in the ecological cabin so as to optimize plant growth conditions; recalculating a plant growth index GI based on the adjusted environmental parameters in the ecological cabin; and evaluating the operation state of the ecological cabin based on the recalculated plant growth index GI. The operation efficiency and stability of the ecological cabin can be improved, and intelligent management of the internal environment of the ecological cabin is achieved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent operation monitoring and management of ecological cabins, and in particular to an operation monitoring method and device of an ecological cabin. Background Art

[0002] In the field of modern agriculture and environmental science, the eco-cabin is an experimental facility that simulates an ecosystem. Its operation monitoring technology is of great significance to ensure the stability of the internal environment of the eco-cabin and the good growth of plants. Existing eco-cabin monitoring technology mainly relies on manual observation and measurement of simple instruments. These methods are often inefficient and have limited accuracy, and it is difficult to achieve real-time and comprehensive monitoring of the internal environmental parameters of the eco-cabin. In addition, traditional methods also have limitations in data analysis and application, and often require professionals to perform complex data processing and interpretation, which is not conducive to the rapid evaluation of the operating status of the eco-cabin and decision support.

[0003] In the process of implementing the embodiments of the present invention, the inventors found that there are at least the following problems or defects in the prior art: first, the prior art lacks the ability to comprehensively monitor multiple environmental parameters inside the eco-cabin, and it is difficult to comprehensively reflect the operating status of the eco-cabin; second, the existing methods have limitations in data processing and application, and cannot achieve rapid evaluation and intelligent decision-making of the operating status of the eco-cabin; in addition, the prior art also lacks automated and intelligent support in environmental parameter adjustment and fault diagnosis, resulting in insufficient operating efficiency and stability of the eco-cabin. Summary of the invention

[0004] The embodiments of the present invention aim to provide an operation monitoring method and device for an eco-cabin to solve the technical problems raised in the prior art.

[0005] The embodiment of the present invention solves the technical problem by adopting the following technical solution:

[0006] In a first aspect, a method for monitoring the operation of an eco-cabin is provided, comprising:

[0007] During the operation of the eco-cabin, the environmental parameters inside the eco-cabin are collected based on the preset sensor array, and the environmental parameters include temperature, humidity, light intensity, and CO2 concentration;

[0008] The growth parameters of the eco-chamber are obtained based on the collected environmental parameters, wherein the growth parameters include photosynthesis efficiency PE and water use efficiency WUE;

[0009] According to the photosynthesis efficiency PE and water use efficiency WUE, the growth index GI of plants inside the ecological cabin is calculated;

[0010] According to the calculated plant growth index GI, the environmental parameters inside the eco-chamber are adjusted to optimize the growth conditions of the plants;

[0011] Recalculate the plant growth index GI based on the adjusted environmental parameters inside the ecological cabin;

[0012] Based on the recalculated plant growth index GI, the operating status of the eco-chamber is evaluated.

[0013] As a further improvement of this application, the calculation formulas for photosynthesis efficiency PE and water use efficiency WUE are:

[0014]

[0015] Among them, P photo =h(I,T,C), represents the photosynthetic rate, W=K(H,T), represents the water consumption, h and k are known functions, I represents the light intensity, T represents the temperature, C represents the CO2 concentration, and H represents the humidity.

[0016] As a further improvement of this application, the following steps are included:

[0017] The plant growth index GI is calculated using the following formula:

[0018] GI=a·PE+b·WUE

[0019] Wherein, a and b are weight coefficients of photosynthesis efficiency and water use efficiency, respectively, and a+b=1.

[0020] As a further improvement of the present application, according to the calculated plant growth index GI, adjusting the environmental parameters inside the eco-cabin includes:

[0021] a. According to the plant growth index GI, use the following to adjust the light intensity inside the eco-chamber:

[0022] I new =I current +k I ·(GI-GI set )

[0023] Among them, I current is the current light intensity, k I is the light intensity adjustment coefficient, GI set is the preset growth index threshold.

[0024] b. According to the plant growth index GI, the CO2 concentration inside the eco-chamber is automatically adjusted using the following formula:

[0025] C new =C current +k C ·(GI-GI set )

[0026] Among them, Ccurrent is the current CO2 concentration, k C is the CO2 concentration adjustment coefficient.

[0027] c. According to the plant growth index GI, the temperature inside the eco-chamber is automatically adjusted using the following formula:

[0028] T new =T current +k T ·(GI-GI set )

[0029] Among them, T current is the current temperature, k T is the temperature adjustment coefficient.

[0030] d. According to the plant growth index GI, the humidity inside the eco-chamber is automatically adjusted using the following formula:

[0031] H new =H current +k H ·(GI-GI set )

[0032] Among them, H current is the current humidity, k H is the humidity adjustment factor.

[0033] As a further improvement of the present application, based on the recalculated plant growth index GI, the evaluation of the operating status of the eco-cabin includes:

[0034] If the recalculated plant growth index GI is higher than the preset threshold, the operating status of the eco-chamber is judged to be good;

[0035] If it is lower than the preset threshold, it is judged that the operating status of the eco-cabin needs to be adjusted.

[0036] As a further improvement of the present application, evaluating the operating status of the eco-cabin includes the following steps:

[0037] The OSI of the eco-cabin is calculated using the following formula:

[0038]

[0039] Among them, GI max is the maximum value of the growth index, GI set is the preset growth index threshold;

[0040] If the OSI value is greater than 0.9, it means that the eco-cabin is in excellent operating condition;

[0041] If the OSI value is less than 0.9 and greater than or equal to 0.5, it means that the eco-chamber is in good operating condition;

[0042] If the OSI value is lower than 0.5, adjust the eco-chamber environmental parameters.

[0043] As a further improvement of the present application, if the OSI value is lower than 0.5, adjusting the environmental parameters of the eco-chamber includes the following steps:

[0044] Re-collect the environmental parameters inside the eco-cabin;

[0045] Recalculate growth parameters;

[0046] Recalculate the plant growth index GI;

[0047] According to the recalculated plant growth index GI, the environmental parameters inside the eco-cabin are adjusted again.

[0048] As a further improvement of the present application, the method further includes:

[0049] If the OSI value is greater than 0.9, collect and record the environmental parameters inside the eco-chamber.

[0050] In a second aspect of the present invention, there is provided an operation monitoring device for an eco-cabin, comprising:

[0051] The environmental parameter acquisition module is used to collect the environmental parameters inside the eco-cabin based on the preset sensor array during the operation of the eco-cabin, and the environmental parameters include temperature, humidity, light intensity, and CO2 concentration;

[0052] A growth parameter calculation module, used to obtain the growth parameters of the eco-chamber based on the collected environmental parameters, wherein the growth parameters include photosynthesis efficiency PE and water use efficiency WUE;

[0053] The growth index calculation module is used to calculate the growth index GI of plants inside the ecological cabin according to the photosynthesis efficiency PE and the water use efficiency WUE;

[0054] The growth condition optimization module is used to adjust the environmental parameters inside the ecological cabin according to the calculated plant growth index GI to optimize the growth conditions of the plants;

[0055] A recalculation module, used to recalculate the plant growth index GI based on the adjusted environmental parameters inside the ecological cabin;

[0056] The operating status evaluation module is used to evaluate the operating status of the ecological cabin based on the recalculated plant growth index GI.

[0057] As a further improvement of the present application, the growth condition optimization module includes:

[0058] The light intensity adjustment unit is used to adjust the light intensity inside the ecological cabin according to the plant growth index GI using the following:

[0059] I new =I current +k I ·(GI-GI set )

[0060] Among them, I current is the current light intensity, k I is the light intensity adjustment coefficient, GI set is the preset growth index threshold.

[0061] The carbon dioxide adjustment unit is used to automatically adjust the CO2 concentration inside the ecological chamber according to the plant growth index GI using the following formula:

[0062] C new =C current +k C ·(GI-GI set )

[0063] Among them, C current is the current CO2 concentration, k C is the CO2 concentration adjustment coefficient.

[0064] The temperature adjustment unit is used to automatically adjust the temperature inside the ecological cabin according to the plant growth index GI using the following formula:

[0065] T new =T current +k T ·(GI-GI set )

[0066] Among them, T current is the current temperature, k T is the temperature adjustment coefficient.

[0067] The humidity adjustment unit is used to automatically adjust the humidity inside the ecological cabin according to the plant growth index GI using the following formula:

[0068] H new =H current +k H ·(GI-GI set )

[0069] Among them, H current is the current humidity, k H is the humidity adjustment factor.

[0070] The above-mentioned embodiments of the present invention have at least the following beneficial effects: The eco-cabin operation monitoring method and device of the present invention can provide a real-time and comprehensive means of monitoring the environmental parameters of the eco-cabin, collect key parameters such as temperature, humidity, light intensity, CO2 concentration, etc. through a preset sensor array, and calculate key growth parameters such as photosynthesis efficiency, water use efficiency and plant growth index. This method can optimize the growth conditions of plants and create an optimal growth environment for plants through real-time adjustment of these parameters, thereby improving the operating efficiency and stability of the eco-cabin. At the same time, the method can also perform pattern recognition on historical data through machine learning algorithms, predict the operating status of the eco-cabin, make adjustments in advance, and further improve the intelligent management level of the eco-cabin.

[0071] In addition, the eco-cabin operation monitoring device of the present invention can effectively evaluate the operating status of the eco-cabin, and display the operating status index in real time through the user interface, providing visual or auditory feedback. When an abnormal index is detected, the alarm system can be automatically triggered, the fault diagnosis program can be started, the possible cause of the fault can be identified, and the environmental parameters can be automatically adjusted according to the diagnosis results to try to restore to the optimal growth conditions. This method can not only improve the safety and reliability of the eco-cabin operation, but also provide maintenance and adjustment suggestions to operators through statistical analysis and predictive maintenance, thereby reducing operating costs and improving the economic benefits of the eco-cabin. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] One or more embodiments are exemplarily described by the figures in the corresponding drawings, and these exemplifications do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0073] Figure 1 It is a flow chart of an operation monitoring method of an eco-cabin provided by an embodiment of the present invention;

[0074] Figure 2 A schematic diagram of the structure of an operation monitoring device for an eco-cabin provided in one embodiment of the present invention;

[0075] Figure 3 The schematic diagram schematically shows the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0076] In order to facilitate the understanding of the present invention, the present invention is described in more detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that when an element is described as "connecting" another element, it can be directly on another element, or there can be one or more centered elements therebetween. The orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "upper end", "lower end", "top" and "bottom" used in this specification is based on the orientation or positional relationship shown in the accompanying drawings, 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 cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0077] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0078] Combine the following Figure 1 , the operation monitoring method 100 of the eco-cabin provided in the embodiment of the present application is described in detail through a specific example.

[0079] Figure 1 : is a flow chart of the operation monitoring method of the eco-capsule provided by the present invention. The operation monitoring method of the eco-capsule provided by one embodiment of the present invention comprises:

[0080] Step 101, during the operation of the eco-cabin, based on a preset sensor array, collecting environmental parameters inside the eco-cabin, the environmental parameters including temperature, humidity, light intensity, and CO2 concentration;

[0081] Step 102, obtaining growth parameters of the eco-chamber based on the collected environmental parameters, wherein the growth parameters include photosynthesis efficiency PE and water use efficiency WUE;

[0082] Step 103, calculating the growth index GI of the plants inside the ecological cabin according to the collected environmental parameters and growth parameters;

[0083] Step 104, adjusting the environmental parameters inside the ecological cabin according to the calculated plant growth index GI to optimize the growth conditions of the plants;

[0084] Step 105, recalculating the plant growth index GI based on the adjusted environmental parameters inside the ecological cabin;

[0085] Step 106: Evaluate the operating status of the eco-chamber based on the recalculated plant growth index GI.

[0086] It should be noted that during the operation of the eco-cabin, the environmental parameters inside the eco-cabin are collected based on the preset sensor array. This means that the eco-cabin will use a series of pre-arranged sensors to collect various environmental data inside the cabin when it is working. The sensor array here refers to a group of different types of sensors that can detect environmental parameters such as temperature, humidity, etc. Environmental parameters here refer to the physical and chemical conditions that affect plant growth.

[0087] Specifically, these sensors may include temperature sensors, humidity sensors, light intensity sensors, and carbon dioxide concentration sensors, which can monitor the environmental status of the eco-cabin in real time. The data collected by these sensors will be used to calculate the growth parameters of the plants, such as estimating the photosynthesis efficiency by measuring light intensity and temperature. During implementation, the type and quantity of sensors, as well as their distribution locations in the eco-cabin, can be set according to the size of the eco-cabin and the type of plants.

[0088] More specifically, preferably, the data collection frequency of these sensors can be set to once per minute to ensure the real-time and accuracy of the data. For example, the temperature sensor can use a high-precision thermocouple sensor, the humidity sensor can use a capacitive or resistive sensor, and the light intensity and CO2 concentration can be measured using a photoresistor and an infrared gas sensor, respectively.

[0089] Furthermore, the data from these sensors can be sent to the central processing unit through a wireless transmission module for further analysis and processing. In addition, the accuracy and measurement range of the sensor also need to be selected according to the specific application scenario of the eco-cabin and the plant growth requirements.

[0090] In some embodiments, the calculation formulas for photosynthesis efficiency PE and water use efficiency WUE are:

[0091]

[0092] Among them, P photo =h(I,T,C) represents the photosynthetic rate, W=k(H,T) represents the water consumption, h and k are known functions, I represents the light intensity, T represents the temperature, C represents the CO2 concentration, and H represents the humidity.

[0093] It should be noted that the calculation formulas for photosynthesis efficiency PE and water use efficiency WUE are respectively PE and WUE in the formula are two key parameters for measuring plant growth efficiency. Photosynthesis efficiency (PE) refers to the efficiency of plants converting light energy into chemical energy through photosynthesis, while water use efficiency (WUE) refers to the amount of dry matter produced by plants through photosynthesis under a certain water consumption. These two parameters are crucial for evaluating plant growth conditions and optimizing the eco-cabin environment.

[0094] Specifically, the photosynthesis efficiency PE can be calculated by the formula PE = Φh (P, T, C), where Φh is a function of light intensity (P), temperature (T) and CO2 concentration (C). The water use efficiency WUE can be calculated by the formula WUE = Ψh (P, H), where Ψh is a function of light intensity (P) and humidity (H). These functions can be established based on experimental data and plant physiological principles. For example, the relationship between these environmental factors and photosynthesis and water use efficiency can be determined by regression analysis.

[0095] Preferably, the specific form of these functions can be adjusted according to different types of plants and growth conditions. For example, for shade-loving plants, the effect of light intensity on photosynthesis efficiency may be different from that of sun-loving plants, so the form of the Φh function may need to be adjusted accordingly. Similarly, for plants growing under different humidity conditions, the Ψh function may also require different parameter settings.

[0096] To provide a concrete calculation process, we can define the functions Φh and Ψh using regression models based on experimental data and plant physiological principles. The following are example forms of these functions:

[0097] PE=Φ h (P,T,C)=a·P b ·T c ·C d

[0098] WUE=Ψ h (P,H)=e·P f ·H g

[0099] Where a, b, c, d, e, f, g are coefficients determined by regression analysis for a specific plant species and growth conditions. For example, if regression analysis shows that photosynthesis efficiency is proportional to the logarithm of light intensity, proportional to the square of temperature, and linearly proportional to CO2 concentration, then the function is:

[0100] PE=0.5·ln(P)·T 2 ·C.

[0101] For example, if regression analysis shows that water use efficiency is linearly proportional to light intensity and proportional to the inverse of humidity, then the function is:

[0102]

[0103] To determine these coefficients, a series of experiments are performed in which the photosynthetic rate and water consumption are measured under different conditions of light intensity, temperature, CO2 concentration, and humidity. These data points can then be used to fit a regression model and estimate the coefficients.

[0104] For example, given the following data points:

[0105] P=100, T=20, C=400, PE=2.5

[0106] P=200, T=25, C=500, PE=5.0

[0107] P=150, T=22, C=450, PE=3.8

[0108] We can use these data points to fit a model and estimate the coefficients a, b, c, d.

[0109] Similarly, for water use efficiency, if we have the following data points:

[0110] P = 100, H = 50, WUE = 0.8

[0111] P = 200, H = 30, WUE = 1.2

[0112] P=150,H=40,WUE=1.0

[0113] You can use these data points to fit a model and estimate the coefficients e, f, and g.

[0114] Furthermore, these functions can also be trained and optimized based on a large amount of environmental and growth data through machine learning methods, such as neural networks, to improve calculation accuracy. In practical applications, the parameters of these functions can be adjusted according to the specific type and growth stage of the plant to achieve accurate calculation of photosynthesis efficiency and water use efficiency.

[0115] In some embodiments, the steps include:

[0116] The plant growth index GI is calculated using the following formula:

[0117] GI=a·PE+b·WUE

[0118] Wherein, a and b are weight coefficients of photosynthesis efficiency and water use efficiency, respectively, and a+b=1.

[0119] It should be noted that the plant growth index (GI) is obtained by weighted summation of photosynthesis efficiency (PE) and water use efficiency (WUE), while α and β are the weights of these two parameters, which add up to 1 to ensure the standardization of the index.

[0120] Specifically, the plant growth index (GI) is a comprehensive indicator used to measure the overall condition of plant growth. The values ​​of α and β can be adjusted according to plant species, growth stage or environmental conditions. For example, for plants growing in arid environments, higher water use efficiency may be required, so the value of β will increase accordingly. The setting of these weight coefficients should be based on experimental data or expert experience to reflect the actual impact of different environmental factors on plant growth.

[0121] Preferably, the calculation of the plant growth index (GI) can be further refined. For example, the values ​​of α and β can be determined by an optimization algorithm, which can find the optimal weight coefficient based on historical data and plant growth models. In addition, it is also possible to consider introducing other environmental parameters, such as soil nutrient content or plant biomass, to further improve the calculation model of GI.

[0122] Furthermore, in actual operation, the values ​​of α and β can be dynamically adjusted according to the specific growth conditions of the plants in the eco-chamber and environmental changes to achieve real-time monitoring and accurate evaluation of the plant growth conditions. Machine learning methods can also be used to allow the system to automatically learn and adjust these weight coefficients to adapt to different growth conditions and improve the prediction accuracy of the growth index.

[0123] In some embodiments, the steps include:

[0124] a. According to the plant growth index GI, the light intensity inside the eco-cabin is automatically adjusted using the following formula:

[0125] I new =I current +k I ·(GI-GI set )

[0126] Among them, I current is the current light intensity, k I is the light intensity adjustment coefficient, GI set is the preset growth index threshold.

[0127] b. According to the plant growth index GI, the CO2 concentration inside the eco-chamber is automatically adjusted using the following formula:

[0128] C new =C current +k C ·(GI-GIset )

[0129] Among them, C current is the current CO2 concentration, k C is the CO2 concentration adjustment coefficient.

[0130] c. According to the plant growth index GI, the temperature inside the eco-chamber is automatically adjusted using the following formula:

[0131] T new =T current +k T ·(GI-GI set )

[0132] Among them, T current is the current temperature, k T is the temperature adjustment coefficient.

[0133] d. According to the plant growth index GI, the humidity inside the eco-chamber is automatically adjusted using the following formula:

[0134] H new =H current +k H ·(GI-GI set )

[0135] Among them, H current is the current humidity, k H is the humidity adjustment factor.

[0136] It should be noted that the following formula is used to automatically adjust the environmental parameters inside the eco-cabin according to the plant growth index GI, which means that the environmental control system of the eco-cabin will automatically adjust the environmental conditions inside the cabin, such as light intensity, CO2 concentration, temperature and humidity, according to the value of the plant growth index (GI) to promote the best growth of plants. The plant growth index (GI) is a comprehensive parameter that reflects the growth status of plants under specific environmental conditions.

[0137] Specifically, the automatic adjustment can be achieved by a set formula. For example, for the adjustment of light intensity, formula I can be used. new =I current +k I ·(GI-GI set ).

[0138] Similarly, the regulation of CO2 concentration, temperature and humidity can also adopt similar formulas, where each parameter has its corresponding adjustment coefficient and threshold. The setting of these adjustment coefficients and thresholds should be based on experimental data and plant growth models to ensure that the adjustment of environmental parameters can effectively respond to the growth needs of plants.

[0139] Preferably, these adjustment formulas can be further refined to include adaptive adjustments for different plant species and growth stages. For example, for the adjustment of light intensity, the light saturation point and light compensation point of the plant can be considered to avoid the occurrence of light inhibition and light starvation. For the adjustment of CO2 concentration, it can be carried out according to the CO2 saturation point and compensation point of the plant to optimize the effect of photosynthesis. The adjustment of temperature and humidity can also be carried out according to the optimal growth temperature and humidity range of the plant.

[0140] Furthermore, these adjustment coefficients and thresholds can be updated regularly to reflect the latest data on environmental changes and plant growth conditions. Adaptive control algorithms can also be introduced to enable the system to self-optimize the adjustment strategy based on real-time data and predictive models to achieve more precise and efficient environmental control.

[0141] In some embodiments, the following steps are also included:

[0142] If the recalculated plant growth index GI is higher than the preset threshold, the operating status of the eco-chamber is judged to be good;

[0143] If it is lower than the preset threshold, it is judged that the operating status of the eco-cabin needs to be adjusted.

[0144] It should be noted that if the recalculated plant growth index GI is higher than the preset threshold, the operating status of the eco-cabin is judged to be good; if it is lower than the preset threshold, the operating status of the eco-cabin is judged to need adjustment. This means that the operation monitoring system of the eco-cabin will judge the operating status of the eco-cabin based on the comparison of the plant growth index (GI) with a pre-set threshold. The plant growth index (GI) is a comprehensive parameter that reflects the growth status of plants in the eco-cabin, and the threshold is a benchmark value used to evaluate the level of GI.

[0145] Specifically, the threshold of the plant growth index GI can be set according to the plant species planted in the eco-chamber, the growth cycle, and the expected growth target. For example, for a specific crop, a higher GI threshold may be required during the vigorous growth period to reflect its healthy growth state. During implementation, multiple thresholds can be set to reflect different levels of growth conditions, such as normal, good, needing attention, or needing adjustment. The setting of these thresholds should be based on historical data, statistical analysis, and expert experience.

[0146] Preferably, the process of evaluating the operating status of the eco-cabin can be further refined, including real-time monitoring and periodic evaluation. For example, a real-time monitoring system can be set up, and when the GI value exceeds the upper threshold, the system will automatically adjust the environmental parameters of the eco-cabin to prevent possible overgrowth or waste of resources. At the same time, a periodic evaluation mechanism can be set up, such as evaluating the GI value every day or every week, to determine the long-term operating trend of the eco-cabin.

[0147] Furthermore, machine learning algorithms can be introduced to automatically learn and optimize threshold settings based on historical GI data and eco-cabin adjustment records to improve the accuracy of assessment and the timeliness of response. It is also possible to consider combining GI with other environmental parameters (such as soil moisture, nutrient levels, etc.) to conduct a comprehensive multi-factor assessment to obtain a more comprehensive analysis of the eco-cabin's operating status.

[0148] In some embodiments, evaluating the operating status of the eco-capsule includes the following steps:

[0149] The OSI of the eco-cabin is calculated using the following formula:

[0150]

[0151] Among them, GI max is the maximum value of the growth index, GI set is the preset growth index threshold;

[0152] The OSI value (Operational Status Index) is an indicator used to evaluate the operating status of the eco-cabin in the operation monitoring of the eco-cabin. It is calculated by comprehensively considering the environmental parameters inside the eco-cabin and the plant growth index (GI). The determination of the OSI value is based on experimental data and experience. Through long-term monitoring of the growth of plants in the eco-cabin and measurement of environmental parameters such as temperature, humidity, light intensity and CO2 concentration, the operating status of the eco-cabin corresponding to different OSI values ​​can be determined.

[0153] Analyze the relationship between OSI value and the operating status of the eco-cabin,

[0154] If the OSI value is greater than 0.9, it means that the eco-cabin is in excellent operating condition;

[0155] If the OSI value is less than 0.9 and greater than or equal to 0.5, it means that the eco-chamber is in good operating condition;

[0156] If the OSI value is lower than 0.5, adjust the eco-chamber environmental parameters.

[0157] If the OSI value is lower than 0.5, adjusting the eco-chamber environmental parameters includes the following steps:

[0158] Re-collect the environmental parameters inside the eco-cabin;

[0159] Recalculate growth parameters;

[0160] Recalculate the plant growth index GI;

[0161] According to the recalculated plant growth index GI, the environmental parameters inside the eco-cabin are adjusted again.

[0162] If the OSI value is greater than 0.9, collect and record the environmental parameters inside the eco-chamber.

[0163] The determination of OSI values ​​is usually based on experimental data and experience. Through long-term observation and data collection of plant growth in the eco-cabin, the operating status of the eco-cabin corresponding to different OSI values ​​can be determined. For example, by monitoring indicators such as plant growth rate, photosynthesis efficiency, and water use efficiency, the impact of eco-cabin environmental parameters on plant growth can be evaluated. In the experiment, it may be found that when the OSI value is greater than 0.9, the plant growth is very good, so this value is set to indicate that the eco-cabin is in excellent operating condition; when the OSI value is between 0.5 and 0.9, the plant growth is good but there is room for improvement, so it is set to a good state; when the OSI value is lower than 0.5, it may mean that the environmental parameters are not conducive to plant growth, and the environmental parameters of the eco-cabin need to be adjusted to optimize growth conditions. These thresholds are determined based on experimental results and understanding of plant growth laws.

[0164] Furthermore, it is also possible to consider introducing other environmental parameters or plant growth indicators, such as soil moisture, nutrient level, etc., to further improve the OSI calculation model so that it can more comprehensively reflect the operating status of the eco-cabin. In addition, a dynamic adjustment mechanism can be set up to adjust the GI according to the actual operation of the eco-cabin and changes in the external environment. max , in order to achieve real-time and dynamic evaluation of the operating status of the eco-cabin.

[0165] In some embodiments, the method further comprises the following steps:

[0166] Display OSI values ​​in real time through the user interface and provide visual or auditory feedback based on changes in OSI values;

[0167] Set the threshold of OSI value. When the OSI value exceeds the preset normal range, the alarm system will be automatically triggered.

[0168] Record historical data of OSI values ​​and automatically start the fault diagnosis program to identify possible fault causes when abnormal OSI values ​​are detected;

[0169] Based on the OSI value and fault diagnosis results, the environmental parameters of the eco-chamber are automatically adjusted to try to restore to the optimal growth conditions.

[0170] It should be noted that the operation monitoring system of the eco-cabin will dynamically display the real-time value of the eco-cabin operating status index (OSI) through a user interface, and when the OSI value changes, the system can remind the operator visually or auditorily. The user interface is a bridge for human-computer interaction, allowing operators to intuitively understand the operating status of the eco-cabin.

[0171] Specifically, the user interface can be a graphical interface that displays real-time data of OSI values ​​and trends over time. Visual feedback may include color changes (e.g., green when the OSI value is close to 1 and red when it is below a threshold), or dynamic updates of charts and indicators. Auditory feedback may be a beep or alarm sound when the OSI value reaches a certain condition. The parameter settings of these feedback mechanisms, such as color coding, sound type, or prompt frequency, can be adjusted according to the needs and preferences of the operator.

[0172] Preferably, the user interface can further integrate more interactive functions. For example, when the OSI value shows that the eco-chamber is not in good operating condition, the interface can provide adjustment suggestions or automatically execute the preset adjustment strategy. In addition, the system can be configured to send a notification to the operator via email or SMS when the OSI value exceeds the preset normal range.

[0173] More specifically, the user interface can include a fault diagnosis tool that automatically starts and provides possible fault causes and solutions when the OSI value is abnormal. A predictive maintenance module can also be implemented to predict future maintenance needs based on historical data of OSI values, so that maintenance work can be scheduled in advance and the risk of unexpected downtime can be reduced. These enhancements can improve the reliability of the eco-cabin operation and the convenience of operation.

[0174] In some embodiments, the following steps are also included:

[0175] Regularly conduct statistical analysis on historical data of OSI values ​​to identify long-term trends in the operating status of the eco-chamber;

[0176] According to the statistical analysis results, adjust the operation strategy of the eco-cabin, such as optimizing the environmental parameter settings, to improve the operation efficiency and stability of the eco-cabin;

[0177] Use machine learning algorithms to perform pattern recognition on historical data of OSI values ​​to predict the future operating status of the eco-cabin and make adjustments in advance;

[0178] Based on the prediction results, maintenance and adjustment recommendations are automatically generated and provided to operators through the user interface.

[0179] It should be noted that in addition to real-time monitoring and feedback of OSI values, the system will also regularly process and analyze OSI historical data in order to discover the changing patterns of the eco-cabin operating status over time. Statistical analysis is a data processing method used to extract useful information from data, while the long-term trend refers to the overall direction of the eco-cabin operating status index over time.

[0180] Specifically, statistical analysis can include calculating statistical parameters such as the mean, standard deviation, maximum and minimum values ​​of the OSI value, as well as drawing a trend chart of the OSI value over time. These analyses can help identify the stability and periodic changes in the operating status of the eco-cabin, thereby providing a basis for maintenance and adjustment. For example, if the analysis shows that the OSI value is continuously low in a specific season or time period, it may indicate that the environmental control strategy of the eco-cabin needs to be adjusted.

[0181] Preferably, the results of the statistical analysis can be used to further optimize the operation strategy of the eco-cabin. For example, if the analysis finds that the OSI value performs poorly under certain conditions, the system can automatically adjust the environmental parameter settings, such as changing the light cycle or adjusting the temperature setting, to improve the operation efficiency of the eco-cabin.

[0182] More specifically, the system can use machine learning algorithms to perform pattern recognition on historical data of OSI values, thereby predicting the future operating status of the eco-cabin and making adjustments in advance. For example, by analyzing historical data, the system may learn to adjust temperature or humidity before weather changes to maintain optimal conditions for plant growth. In addition, the system can also automatically generate maintenance and adjustment recommendations based on the prediction results and provide them to operators through the user interface, allowing operators to take timely actions to optimize the operation of the eco-cabin.

[0183] The above-mentioned embodiments of the present invention have the following beneficial effects: The eco-cabin operation monitoring method of the present invention can monitor the growth status of plants in real time and optimize the growth conditions by collecting the environmental parameters inside the eco-cabin and calculating the growth parameters. This method uses photosynthesis efficiency and water use efficiency to calculate the plant growth index, and then adjusts the environmental parameters of the eco-cabin, which can not only improve the growth efficiency of plants, but also achieve refined management and reduce resource waste. In addition, by monitoring the changes in the plant growth index, the environmental conditions of the eco-cabin can be adjusted in time to ensure that the plants are always in the best growth state, thereby improving the operating efficiency and ecological value of the eco-cabin.

[0184] In addition, the present invention also provides an eco-cabin operation status evaluation mechanism based on the plant growth index, which can effectively judge the operation status of the eco-cabin and make timely adjustments. When the plant growth index exceeds the preset threshold, it indicates that the eco-cabin is in good operation and no additional intervention is required; when the index is lower than the threshold, it indicates that the environmental parameters of the eco-cabin need to be adjusted to promote better plant growth. This evaluation mechanism can not only help operators make decisions quickly, but also provide a scientific basis for the long-term operation of the eco-cabin through the calculation and analysis of the eco-cabin operation status index, further optimize the eco-cabin operation strategy, and improve its stability and sustainability.

[0185] like Figure 2As shown, in some embodiments, an operation monitoring device 200 of an eco-cabin includes:

[0186] Environmental parameter collection module 201, used to collect environmental parameters such as temperature, humidity, light intensity, CO2 concentration, etc. inside the ecological cabin;

[0187] A growth parameter calculation module 202 is used to calculate the growth parameters of the eco-chamber based on the collected environmental parameters, including photosynthetic rate and water use efficiency;

[0188] The plant growth index calculation module 203 is used to calculate the plant growth index GI according to the growth parameters;

[0189] The environmental parameter adjustment module 204 is used to automatically adjust the environmental parameters inside the ecological cabin according to the plant growth index GI;

[0190] An operation status evaluation module 205 is used to evaluate the operation status of the ecological cabin based on the recalculated plant growth index GI;

[0191] The user interface module 206 is used to display the OSI value in real time and provide feedback, as well as receive adjustment instructions from operators.

[0192] It is understandable that the modules recorded in the operation monitoring device 200 of the eco-cabin are similar to those in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the operation monitoring method of the eco-capsule are also applicable to the operation monitoring device 200 of the eco-capsule and the modules contained therein, and will not be described in detail here.

[0193] In some embodiments, the evaluation results in the operating status evaluation module include:

[0194] If the plant growth index GI is higher than the preset threshold, a signal indicating that the eco-cabin is in good operating condition is output;

[0195] If it is lower than the preset threshold, a signal is output that the eco-cabin operation status needs to be adjusted;

[0196] The user interface module can display the OSI value, receive adjustment instructions from operators, and provide corresponding feedback according to changes in the OSI value.

[0197] It should be noted that the operation monitoring device of the eco-cabin collects data on various environmental factors in the eco-cabin through a special module, which is essential for monitoring and controlling the growth environment of plants in the eco-cabin. The environmental parameter acquisition module is part of the device and is responsible for real-time monitoring and recording of multiple environmental variables in the eco-cabin.

[0198] Specifically, the environmental parameter acquisition module may include a variety of sensors, such as temperature sensors, humidity sensors, light intensity sensors, and carbon dioxide concentration sensors, which can accurately measure the relevant environmental parameters in the eco-cabin. The setting of parameters will depend on the type and growth requirements of the plants in the eco-cabin, as well as the design specifications of the eco-cabin. For example, the temperature sensor may need to be set to a specific measurement range and accuracy to ensure that it can adapt to possible temperature changes in the eco-cabin.

[0199] Preferably, the environmental parameter acquisition module can integrate a microprocessor to process the data collected by the sensor and convert it into a format that can be used for monitoring and analysis. In addition, the module may also include a data storage function to save historical data for a long time for future analysis and comparison.

[0200] More specifically, the module can be designed to transmit data wirelessly, enabling it to send information to a central processing system over long distances, thereby enabling remote monitoring and control. It is also possible to consider adding a user-defined function that allows operators to adjust the sensor's measurement range and reporting frequency according to specific needs or conditions to increase the flexibility and adaptability of the monitoring device.

[0201] Reference below Figure 3 , which shows a schematic diagram of a structure 300 of an electronic device suitable for implementing some embodiments of the present invention. The electronic devices in some embodiments of the present invention may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The terminal device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0202] like Figure 3 As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0203] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication devices 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0204] Furthermore, the storage medium of the embodiment of the present application stores program instructions that can implement all the above methods, wherein the program instructions can be stored in the above storage medium in the form of a software product, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.

[0205] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Under the concept of the present invention, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes in different aspects of the present invention as above, which are not provided in detail for the sake of simplicity. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the operation of an ecological cabin, characterized in that: The following steps are involved: During the operation of the eco-cabin, the environmental parameters inside the eco-cabin are collected based on the preset sensor array, and the environmental parameters include temperature, humidity, light intensity, and CO2 concentration; The growth parameters of the eco-chamber are obtained based on the collected environmental parameters, wherein the growth parameters include photosynthesis efficiency PE and water use efficiency WUE; According to the photosynthesis efficiency PE and water use efficiency WUE, the growth index GI of plants inside the ecological cabin is calculated; According to the calculated plant growth index GI, the environmental parameters inside the eco-chamber are adjusted to optimize the growth conditions of the plants; Recalculate the plant growth index GI based on the adjusted environmental parameters inside the ecological cabin; Based on the recalculated plant growth index GI, the operating status of the eco-chamber is evaluated.

2. The method for monitoring the operation of the ecological cabin according to claim 1, characterized in that: The calculation formulas for photosynthesis efficiency PE and water use efficiency WUE are: Among them, P photo =h(I,T,C), represents the photosynthetic rate, W=k(H,T), represents the water consumption, h and k are known functions, I represents the light intensity, T represents the temperature, C represents the CO2 concentration, and H represents the humidity.

3. The method for monitoring the operation of the ecological cabin according to claim 2, characterized in that: The following steps are involved: The plant growth index GI is calculated using the following formula: GI=a·PE+b·WUE Wherein, a and b are weight coefficients of photosynthesis efficiency and water use efficiency, respectively, and A+b=1.

4. The method for monitoring the operation of the ecological cabin according to claim 1, characterized in that: According to the calculated plant growth index GI, the environmental parameters inside the eco-cabin are adjusted to include: a. According to the plant growth index GI, use the following to adjust the light intensity inside the eco-chamber: IN new =I current +k I ·(GI-GI set ) Among them, I current is the current light intensity, k I is the light intensity adjustment coefficient, GI set is the preset growth index threshold; b. According to the plant growth index GI, the CO2 concentration inside the eco-chamber is automatically adjusted using the following formula: C new =C current +k C ·(GI-GI set ) Among them, C current is the current CO2 concentration, k C is the CO2 concentration adjustment coefficient; c. According to the plant growth index GI, the temperature inside the eco-chamber is automatically adjusted using the following formula: T new =T current +k T ·(GI-GI set ) Among them, T current is the current temperature, k T is the temperature regulation coefficient; d. According to the plant growth index GI, the humidity inside the eco-chamber is automatically adjusted using the following formula: H new =H current +k H ·(GI-GI set ) Among them, H current is the current humidity, k H is the humidity adjustment factor.

5. The method for monitoring the operation of the ecological cabin according to claim 1, characterized in that: Based on the recalculated plant growth index GI, the operating status of the eco-cabin is evaluated including: If the recalculated plant growth index GI is higher than the preset threshold, the operating status of the eco-chamber is judged to be good; If it is lower than the preset threshold, it is judged that the operating status of the eco-cabin needs to be adjusted.

6. The method for monitoring the operation of the ecological cabin according to claim 5, characterized in that: Evaluating the operating status of the eco-cabin includes the following steps: The OSI of the eco-cabin is calculated using the following formula: Among them, GI max is the maximum value of the growth index, GI set is the preset growth index threshold; If the OSI value is greater than 0.9, it means that the eco-cabin is in excellent operating condition; If the OSI value is less than 0.9 and greater than or equal to 0.5, it means that the eco-chamber is in good operating condition; If the OSI value is lower than 0.5, adjust the eco-chamber environmental parameters.

7. The method for monitoring the operation of the ecological cabin according to claim 6, characterized in that: If the OSI value is lower than 0.5, adjust the eco-cabin environmental parameters The following steps are involved: Re-collect the environmental parameters inside the eco-cabin; Recalculate growth parameters; Recalculate the plant growth index GI; According to the recalculated plant growth index GI, the environmental parameters inside the eco-cabin are adjusted again.

8. The method for monitoring the operation of the ecological cabin according to claim 7, characterized in that: The method further comprises: If the OSI value is greater than 0.9, collect and record the environmental parameters inside the eco-chamber.

9. An operation monitoring device for an eco-cabin, characterized in that: include: The environmental parameter acquisition module is used to collect the environmental parameters inside the eco-cabin based on the preset sensor array during the operation of the eco-cabin, and the environmental parameters include temperature, humidity, light intensity, and CO2 concentration; A growth parameter calculation module, used to obtain the growth parameters of the eco-chamber based on the collected environmental parameters, wherein the growth parameters include photosynthesis efficiency PE and water use efficiency WUE; The growth index calculation module is used to calculate the growth index GI of plants inside the ecological cabin according to the photosynthesis efficiency PE and the water use efficiency WUE; The growth condition optimization module is used to adjust the environmental parameters inside the ecological cabin according to the calculated plant growth index GI to optimize the growth conditions of the plants; A recalculation module, used to recalculate the plant growth index GI based on the adjusted environmental parameters inside the ecological cabin; The operating status evaluation module is used to evaluate the operating status of the ecological cabin based on the recalculated plant growth index GI.

10. The operation monitoring device of the ecological cabin according to claim 9, characterized in that: The growth condition optimization module comprises: The light intensity adjustment unit is used to adjust the light intensity inside the ecological cabin according to the plant growth index GI using the following: IN new =I current +k I ·(GI-GI set ) Among them, I current is the current light intensity, k I is the light intensity adjustment coefficient, GI set is the preset growth index threshold; The carbon dioxide adjustment unit is used to automatically adjust the CO2 concentration inside the ecological chamber according to the plant growth index GI using the following formula: C new =C current +k C ·(GI-GI set ) Among them, C current is the current CO2 concentration, k C is the CO2 concentration adjustment coefficient; The temperature adjustment unit is used to automatically adjust the temperature inside the ecological cabin according to the plant growth index GI using the following formula: T new =T current +k T ·(GI-GI set ) Among them, T current is the current temperature, k T is the temperature regulation coefficient; The humidity adjustment unit is used to automatically adjust the humidity inside the ecological cabin according to the plant growth index GI using the following formula: H new =H current +k H ·(GI-GI set ) Among them, H current is the current humidity, k H is the humidity adjustment factor.

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