An intelligent cultivation room for Tremella cultivation

Abstract

The present invention discloses an intelligent cultivation room for Tremella fuciformis (tremella) cultivation. The room comprises a control module, a display module, multiple monitoring module groups, and multiple cultivation equipment, each of which is communicatively connected to the control module. The control module is communicatively connected to a cloud platform. Each monitoring module group includes a temperature sensor, an upper air humidity sensor, a middle air humidity sensor, a soil moisture sensor, an illumination sensor, an image acquisition module, and a carbon dioxide sensor. The cultivation equipment includes a temperature control unit, a lighting unit, a ventilation unit, a spray unit, and an irrigation unit. The technical solution proposed in the present invention aims to achieve intelligent control during the Tremella fuciformis cultivation process.

Description

Technical Field

[0001] The invention relates to the technical field of cultivation rooms, and in particular to an intelligent cultivation room for cultivating tremella. Background Art

[0002] Tremella fuciformis is a fruiting body of the fungus of the phylum Basidiomycota, class Tremellales, order Tremellaceae, and genus Tremella. It is also known as white fungus, snow fungus, and tremella. It has the reputation of "the crown of fungi". It is generally chrysanthemum-shaped or cockscomb-shaped, with a diameter of 5-10 cm, soft, white, translucent, and elastic. As a traditional edible fungus, it has always been a food deeply loved by the people.

[0003] Tremella fuciformis is a mesophilic fungus. The cultivation process of Tremella fuciformis is inseparable from the accompanying mycelium of Tremella fuciformis. Its mixed mycelium is not resistant to high temperatures, but can withstand low temperatures.

[0004] Tremella growth includes the mycelium germination period and the mycelium growth period.

[0005] Mycelium germination period: Mycelium can grow between 15 and 30 degrees Celsius, but the temperature should not exceed 30 degrees Celsius. It is most suitable to control it between 23 and 25 degrees Celsius. Because when the temperature is higher than 30 degrees Celsius, the mycelium of the incense ash fungus will be in an abnormal state and grow too fast. When the temperature is lower than 20 degrees Celsius, the mycelium of the incense ash fungus grows too slowly.

[0006] Mycelial Growth Stage: Due to the mycelial germination stage, the temperature inside the bag rises slightly. Adjust the temperature appropriately, lowering the room temperature by 2-3°C. When the ambient temperature is above 28°C, black droplets will form at the inoculation hole, causing pedicle rot. When the temperature is below 18°C, white, crystalline mucus will form at the hole, also causing the base of the fungus to rot. Tremella fuciformis is very cold-resistant, and spores can survive germination at 0°C for 2 hours without losing their ability to germinate.

[0007] Tremella fuciformis spores germinate into hyphae at a relative humidity of 70% to 80%, which then grow and differentiate into fruiting bodies. Fruiting bodies develop rapidly at a relative humidity of 80% to 90%. If the relative humidity exceeds 90%, germination is difficult and they emerge as buds. The resulting hyphae are weak, thin, and sparse, and the fruiting bodies are poorly differentiated or gelatinize into clumps.

[0008] In addition, the growth process of Tremella fuciformis requires good ventilation conditions.

[0009] Since the various cultivation conditions during the Tremella fuciformis growth cycle need to be adjusted accordingly, and it is difficult for ordinary people to grasp the specific range of cultivation conditions that is more optimal in each cycle, the cultivation conditions are difficult for ordinary people to control. If the control is not good, it will easily lead to a reduction in Tremella fuciformis production.

[0010] In the existing technology, the conditions for growing Tremella fuciformis generally rely on manual and experience-based adjustments, but relying on manual and experience-based adjustments makes it difficult to increase production. Therefore, it is necessary to propose an intelligent cultivation room for Tremella fuciformis cultivation to achieve intelligent control during the Tremella fuciformis cultivation process. Summary of the Invention

[0011] The main purpose of the present invention is to provide an intelligent cultivation room for Tremella fuciformis cultivation, aiming to propose an intelligent cultivation room for Tremella fuciformis cultivation to achieve intelligent control during the Tremella fuciformis cultivation process.

[0012] To achieve the above-mentioned object, the present invention proposes an intelligent cultivation room for Tremella fuciformis cultivation, wherein the cultivation room is provided with a control module and a display module respectively connected to the control module, a plurality of monitoring module groups and a plurality of cultivation devices; the control module is connected to the cloud platform;

[0013] Each monitoring module group includes a temperature sensor, an upper layer air humidity sensor, a middle layer air humidity sensor, a soil moisture sensor, a light intensity sensor, an image acquisition module and a carbon dioxide sensor; the various planting points in the cultivation room are distributed in a dot matrix form, and the monitoring module groups are distributed at different monitoring points in the cultivation room;

[0014] The cultivation equipment includes a temperature regulating unit, a lighting unit, a ventilation unit, a spray unit and an irrigation unit; the cultivation equipment is distributed in different cultivation areas of the cultivation room according to the effective range; wherein, each cultivation area is provided with multiple planting points;

[0015] The control module is used to control the monitoring module group to start according to the set collection frequency, so as to collect monitoring data and send it to the cloud platform. The cloud platform determines the growth advantage points and growth disadvantage points from each planting point based on the image data collected by the image collection module, and forms a distribution map of the growth advantage points and growth disadvantage points in the cultivation room; the cloud platform is also used to calculate the advantageous environment data based on the growth advantage points, and calculate the disadvantageous environment data based on the growth disadvantage points;

[0016] The control module is also used to receive the distribution map of growth advantage points and growth disadvantage points, advantageous environment data and disadvantageous environment data sent by the cloud platform for display on the display module, and control the cultivation equipment according to the advantageous environment data to adjust the environmental data of the growth disadvantage points.

[0017] Preferably, the cloud platform includes an image processing unit, a marking unit, a space simulation unit and a data processing unit;

[0018] The image processing unit is used to form a three-dimensional model of the cultivation room and mark the Tremella cultivation images collected from different monitoring points in the three-dimensional model;

[0019] The marking unit is used to mark the monitoring data collected from different monitoring points in a three-dimensional grid, so that the monitoring data of different monitoring points are marked in different grid points of the three-dimensional grid of the three-dimensional model;

[0020] The space simulation unit is used to simulate and distribute the monitoring data marked by the three-dimensional grid into the three-dimensional space of the three-dimensional model to form a three-dimensional cultivation environment monitoring model of the cultivation room;

[0021] The data processing unit is used to convert the Tremella cultivation images collected at different monitoring points into simulated growth results corresponding to the three-dimensional cultivation environment monitoring model.

[0022] Preferably, the Tremella fuciformis is planted at equal distances in the horizontal direction and in the vertical direction at each planting point in the cultivation room; the data processing unit comprises: an image segmentation subunit, a size analysis subunit and a size simulation subunit;

[0023] The image segmentation subunit is used to segment the Tremella cultivation image collected at each monitoring point into longitudinal space and transverse space according to the set segmentation requirements to form a segmented image corresponding to each planting point;

[0024] The size analysis subunit is used to analyze and calculate the size of the Tremella fuciformis in each segmented image;

[0025] The size simulation subunit is used to simulate the Tremella size corresponding to each segmented image into the three-dimensional cultivation environment monitoring model.

[0026] Preferably, the cloud platform further includes a statistical unit: the statistical unit is used to:

[0027] According to the simulated growth results of the Tremella fuciformis size in the three-dimensional cultivation environment monitoring model, the growth results of the reference Tremella fuciformis size are compared, and the planting points corresponding to the simulated growth results exceeding the first preset value of the reference Tremella fuciformis size are regarded as the growth advantage points, and the planting points corresponding to the simulated growth results less than the second preset value of the reference Tremella fuciformis size are regarded as the growth disadvantage points;

[0028] According to the growth advantage points and growth disadvantage points simulated in the three-dimensional cultivation environment monitoring model, a distribution map of the growth advantage points and growth disadvantage points in the cultivation room is formed.

[0029] Preferably, the cloud platform further comprises a data collection unit and a difference analysis unit;

[0030] The data collection unit is used to arrange the monitoring data of each growth advantage point into a first array, and the monitoring data of all growth advantage points are arranged into a first data set; and is used to arrange the monitoring data of each growth disadvantage point into a second array, and the monitoring data of all growth disadvantage points are arranged into a second data set, wherein each first array and each second array respectively include simulated monitoring temperature, simulated monitoring humidity, simulated monitoring soil moisture content, simulated monitoring light intensity and simulated monitoring carbon dioxide concentration;

[0031] The difference analysis unit is used for:

[0032] Analyze the data types with consistency and the data types with differences in each first array of the first data set; regard the data types with consistency as high-interference data types, and regard the data types with differences as low-interference data types;

[0033] Determining whether the monitoring data corresponding to the high-interference data type in the second array is within a set first standard range;

[0034] If the first standard interval is exceeded, the cultivation equipment of the corresponding planting points of the second array is started to adjust the monitoring data of the high-interference data type to the set first standard interval through the cultivation equipment of the corresponding planting points of the second array;

[0035] If it is in the first standard range, determining whether the monitoring data of the corresponding low-interference data type in the second array is in the set second standard range;

[0036] If the second standard interval is exceeded, the cultivation equipment of the second array of corresponding planting points is started to adjust the monitoring data of the low-interference data type to the set second standard interval through the cultivation equipment of the second array of corresponding planting points;

[0037] If it is in the second standard range, mark the second array and mark the planting point corresponding to the second array as an abnormal planting point.

[0038] Preferably, the cloud platform further includes an analysis unit, which is used to:

[0039] Obtaining changes in the growth advantage point area with the acquisition frequency, and obtaining changes in the growth disadvantage point area with the acquisition frequency; wherein the growth disadvantage point will adjust the environmental data through the cultivation equipment;

[0040] Obtain the overlapping areas of growth disadvantage points under different acquisition frequencies;

[0041] Sending the overlapping area to a display module for display;

[0042] Obtain the overlapping areas under different planting round numbers and compare the overlapping ranges of the overlapping areas.

[0043] Preferably, the analysis unit is further used for:

[0044] In the planting area, the first area is obtained by taking the union of the areas of each growth disadvantage point;

[0045] Performing a difference operation between the first area and the overlapping range to obtain the inferior area;

[0046] The disadvantageous area is sent to the display module for display.

[0047] Preferably, the analysis unit is further used for:

[0048] Get the number of the first planting points within the overlapping range;

[0049] The dominant area within the preset radius of the overlapping range is taken as the target area, and the number of second planting points in the target area is obtained;

[0050] Calculate the planting density of the target area after merging the number of first planting points within the overlapping range into the target area;

[0051] When the planting density does not exceed the set density, an adjusted distribution map of each planting point in the target area is obtained according to the sum of the number of the first planting points and the number of the second planting points;

[0052] The adjustment distribution graph is sent to the display module for display.

[0053] Preferably, the simulated monitoring data of each planting point is calculated based on the monitoring data collected by the monitoring points near the planting point. The specific calculation process is as follows:

[0054] Get the distance data between the i-th planting point and each monitoring point, and form an ascending set of distances of monitoring points for the i-th planting point:

[0055] Y i =sort{L i1 ,…,L im ,…,L iM};

[0056] Among them, Y i is the distance ascending set of the i-th planting point, L im is the distance between the mth monitoring point and the ith planting point; 1≤m≤M, M is the number of monitoring points; 1≤i≤I, I is the number of planting points;

[0057] From the distance ascending set of the i-th planting point, select the top three monitoring points as the reference point set:

[0058] A i ={D i1 , D i2,D i3};

[0059] Among them, A i is the reference point set of the i-th planting point, D i1 is the monitoring point closest to the i-th planting point, D i2 is the second closest monitoring point to the i-th planting point, D i3 is the third closest monitoring point to the i-th planting point;

[0060] Based on the monitoring data collected by the top three monitoring points, the simulated monitoring temperature, simulated monitoring humidity, simulated monitoring soil moisture content, simulated monitoring light intensity and simulated monitoring carbon dioxide concentration of the i-th planting point are calculated:

[0061]

[0062] Among them, t i is the simulated monitoring temperature of the i-th planting point, Monitoring point D i1 The collected temperature, δ1 is the first temperature influencing factor; Monitoring point D i2 The collected temperature, δ2 is the second temperature influencing factor; Monitoring point D i3 The collected temperature, δ3 is the third temperature influencing factor; δ1+δ2+δ3=1, δ1>δ2>δ3>0; Δt i is the temperature correction parameter of the i-th planting point;

[0063]

[0064] Among them, r i is the simulated monitoring humidity of the i-th planting point, Monitoring point D i1 The humidity is collected by the humidity sensor closest to the i-th planting point, and λ1 is the first humidity influencing factor; Monitoring point D i1 The humidity collected by the humidity sensor that is second closest to the i-th planting point, λ2 is the second humidity influencing factor; Monitoring point D i2 The humidity collected by the humidity sensor closest to the i-th planting point, λ3 is the third humidity influencing factor; λ1+λ2+λ3=1, λ1>λ2>λ3>0; Δr i is the humidity correction parameter of the i-th planting point;

[0065]

[0066] Among them, b iis the simulated monitored soil moisture content of the i-th planting point; α1 is the first moisture content influencing factor, Monitoring point D i1 The collected soil moisture content, α2 is the second moisture content influencing factor, Monitoring point D i2 The collected soil moisture content, α3 is the third moisture content influencing factor, Monitoring point D i3 The collected soil moisture content; α1+α2+α3=1, α1>α2>α3>0; Δb i is the moisture content correction parameter of the i-th planting point;

[0067]

[0068] Among them, c i is the simulated monitoring light intensity of the i-th planting point; β1 is the first light intensity influencing factor, Monitoring point D i1 The collected illuminance, β2 is the second illuminance influencing factor, Monitoring point D i2 The collected illuminance, β3 is the third illuminance influencing factor, Monitoring point D i3 Collected illuminance; β1+β2+β3=1, β1>β2>β3, Δc i Set the corrected illumination for the i-th planting point;

[0069]

[0070] Among them, e i The simulated monitored carbon dioxide concentration for the i-th planting site, Monitoring point D i1 The collected carbon dioxide concentration, θ1 is the first carbon dioxide concentration influencing factor; Monitoring point D i2 The collected carbon dioxide concentration, θ2 is the second carbon dioxide concentration influencing factor; Monitoring point D i3 The collected carbon dioxide concentration, θ3 is the third carbon dioxide concentration influencing factor; θ1+θ2+θ3=1, θ1>θ2>θ3, Δe i is the CO2 concentration correction parameter for the i-th planting site.

[0071] Preferably, the monitoring data of the j-th growth advantage point are arranged into a first array as follows:

[0072] (t 1j ,r 1j ,b 1j ,c 1j ,e1j );

[0073] Where, 0≤j≤J≤I, j is the serial number of the growth advantage point, J is the number of growth advantage points; t 1j is the simulated monitoring temperature of the jth growth advantage point, r 1j is the simulated monitoring humidity of the jth growth advantage point, b 1j is the simulated monitoring soil moisture content of the jth growth advantage point, c 1j is the simulated monitoring illumination of the jth growth advantage point, e 1j Simulated monitoring of CO2 concentration for the jth growth advantage site;

[0074] The first data set is:

[0075]

[0076] The second array formed by the monitoring data of the k-th growth disadvantage point is:

[0077] (t 2k ,r 2k ,b 2k ,c 2k ,e 2k );

[0078] Where, 0≤k≤K≤I, k is the serial number of the growth disadvantage point, K is the number of growth disadvantage points; t 2k is the simulated monitoring temperature of the kth growth disadvantage point, r 2k is the simulated monitoring humidity of the kth growth disadvantage point, b 2k is the simulated monitoring soil moisture content of the kth growth disadvantage point, c 2k is the simulated monitoring illumination of the kth growth disadvantage point, e 2k Simulated monitoring of CO2 concentration for the kth growth disadvantage site;

[0079] The second data set is:

[0080]

[0081] The consistency of data of one data type in each first array requires the following conditions to be met:

[0082]

[0083]

[0084] Where X is taken from {t, r, b, c, e}, A1 is the first reference value, A1>0;

[0085] If the data of a data type in each first array is different, the following conditions must be met:

[0086]

[0087] Wherein, A2 is the second reference value, A2>A1.

[0088] In the technical solution of the present invention, the monitoring module group is distributed in different monitoring points of the cultivation room to collect temperature data, upper humidity data, middle humidity data, bottom soil moisture data, illuminance data, Tremella growth image and carbon dioxide concentration of each monitoring point; a plurality of Tremella planting points are set in the length direction, width direction and height direction of the cultivation room, and the monitoring module group collects the monitoring data of each planting point at different monitoring points, so as to simulate the temperature, humidity, illuminance, growth conditions and carbon dioxide concentration of different positions in the cultivation room, which is conducive to simulating the environmental data of different planting points in the cultivation room and understanding the promotion of Tremella growth by environmental data; further, the cultivation room is divided into a plurality of cultivation areas, and each cultivation area is provided with cultivation equipment, which is used to adjust the temperature conditions, Humidity conditions, soil moisture, light conditions and ventilation conditions; the control module controls the monitoring equipment to collect monitoring data and send it to the cloud platform. The cloud platform analyzes the growth advantage points and growth disadvantage points in the cultivation room based on the monitoring data, and obtains the distribution map of the growth advantage points and growth disadvantage points to understand the growth of Tremella fuciformis at each planting point in the cultivation room; and the cloud platform is also used to obtain the monitoring data of the growth advantage points and the monitoring data of the growth disadvantage points; these monitoring data and distribution maps are sent to the display module for display to prompt the user to the growth status of Tremella fuciformis in the cultivation room and the environmental data of each planting point, which is conducive to adjusting the environmental data of the growth disadvantage points with reference to the monitoring data of each growth advantage point according to the distribution map of the growth advantage and disadvantage positions and the monitoring data of the growth advantage points, so as to realize intelligent control in the Tremella fuciformis cultivation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0090] Figure 1 This is a structural schematic diagram of an embodiment of an intelligent cultivation room for Tremella fuciformis cultivation according to the present invention;

[0091] Figure 2Schematic diagram of the three-dimensional grid of the cultivation room (cultivation equipment and monitoring module groups are distributed in different positions of the three-dimensional grid).

[0092] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0093] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0094] See also Figures 1 to 2 To achieve the above-mentioned object, the present invention proposes an intelligent cultivation room for Tremella fuciformis cultivation, wherein the cultivation room is provided with a control module and a display module respectively connected to the control module for communication, a plurality of monitoring module groups and a plurality of cultivation devices; the control module is connected to the cloud platform for communication;

[0095] Each monitoring module group includes a temperature sensor, an upper layer air humidity sensor, a middle layer air humidity sensor, a soil moisture sensor, a light intensity sensor, an image acquisition module and a carbon dioxide sensor; the various planting points in the cultivation room are distributed in a dot matrix form, and the monitoring module groups are distributed at different monitoring points in the cultivation room;

[0096] The cultivation equipment includes a temperature regulating unit, a lighting unit, a ventilation unit, a spray unit and an irrigation unit; the cultivation equipment is distributed in different cultivation areas of the cultivation room according to the effective range; wherein, each cultivation area is provided with multiple planting points;

[0097] The control module is used to control the monitoring module group to start according to the set collection frequency, so as to collect monitoring data and send it to the cloud platform. The cloud platform determines the growth advantage points and growth disadvantage points from each planting point based on the image data collected by the image collection module, and forms a distribution map of the growth advantage points and growth disadvantage points in the cultivation room; the cloud platform is also used to calculate the advantageous environment data based on the growth advantage points, and calculate the disadvantageous environment data based on the growth disadvantage points;

[0098] The control module is also used to receive the distribution map of growth advantage points and growth disadvantage points, advantageous environment data and disadvantageous environment data sent by the cloud platform for display on the display module, and control the cultivation equipment according to the advantageous environment data to adjust the environmental data of the growth disadvantage points.

[0099] In the technical solution of the present invention, the monitoring module group is distributed in different monitoring points of the cultivation room to collect temperature data, upper humidity data, middle humidity data, bottom soil moisture data, illuminance data, Tremella growth image and carbon dioxide concentration of each monitoring point; a plurality of Tremella planting points are set in the length direction, width direction and height direction of the cultivation room, and the monitoring module group collects the monitoring data of each planting point at different monitoring points, so as to simulate the temperature, humidity, illuminance, growth conditions and carbon dioxide concentration of different positions in the cultivation room, which is conducive to simulating the environmental data of different planting points in the cultivation room and understanding the promotion of Tremella growth by environmental data; further, the cultivation room is divided into a plurality of cultivation areas, and each cultivation area is provided with cultivation equipment, which is used to adjust the temperature conditions, Humidity conditions, soil moisture, light conditions and ventilation conditions; the control module controls the monitoring equipment to collect monitoring data and send it to the cloud platform. The cloud platform analyzes the growth advantage points and growth disadvantage points in the cultivation room based on the monitoring data, and obtains the distribution map of the growth advantage points and growth disadvantage points to understand the growth of Tremella fuciformis at each planting point in the cultivation room; and the cloud platform is also used to obtain the monitoring data of the growth advantage points and the monitoring data of the growth disadvantage points; these monitoring data and distribution maps are sent to the display module for display to prompt the user to the growth status of Tremella fuciformis in the cultivation room and the environmental data of each planting point, which is conducive to adjusting the environmental data of the growth disadvantage points with reference to the monitoring data of each growth advantage point according to the distribution map of the growth advantage and disadvantage positions and the monitoring data of the growth advantage points, so as to realize intelligent control in the Tremella fuciformis cultivation process.

[0100] Specifically, the cultivation room can adopt the log planting method or other methods. If the log planting method is adopted, the planting point is opened on the log, and if other planting methods are adopted, the planting point is set according to needs.

[0101] Specifically, the cultivation room includes a Tremella fuciformis (tremella) growing area. Within the Tremella fuciformis (tremella) growing area, each planting point can be arranged in rows and columns according to a predetermined rule to form a dot matrix. Multiple monitoring module groups are distributed at different monitoring points in the cultivation room, allowing different monitoring module groups to collect monitoring data within each dot matrix area. This monitoring data includes environmental data and Tremella fuciformis growth image data.

[0102] The cultivation equipment is also divided into multiple groups, and one cultivation equipment is set in each cultivation area. The effective range of the cultivation equipment is determined by the intersection of the respective ranges of action of the temperature control unit, the lighting unit, the ventilation unit, the spray unit, and the irrigation unit. After determining the intersection of the respective ranges of action, the dot matrix area is divided according to the range of action to divide the cultivation room into multiple non-overlapping cultivation areas.

[0103] The cultivation areas are divided as follows:

[0104] Get the effective range of the cultivation equipment:

[0105] A=A1∩A2∩A3∩A4∩A5;

[0106] Among them, A is the intersection of the operating ranges of each device in the cultivation equipment, that is, the effective operating range; A1 is the operating range of the temperature adjustment unit; A2 is the operating range of the lighting unit; A3 is the operating range of the ventilation unit; A4 is the operating range of the spray unit; A5 is the operating range of the irrigation unit;

[0107] Calculate the number of cultivation equipment:

[0108]

[0109] Where S is the area of ​​the cultivation area and N is the number of cultivation equipment.

[0110] Preferably, the cloud platform includes an image processing unit, a marking unit, a space simulation unit and a data processing unit;

[0111] The image processing unit is used to form a three-dimensional model of the cultivation room and mark the Tremella cultivation images collected from different monitoring points in the three-dimensional model;

[0112] The marking unit is used to mark the monitoring data collected from different monitoring points in a three-dimensional grid, so that the monitoring data of different monitoring points are marked in different grid points of the three-dimensional grid of the three-dimensional model;

[0113] The space simulation unit is used to simulate and distribute the monitoring data marked by the three-dimensional grid into the three-dimensional space of the three-dimensional model to form a three-dimensional cultivation environment monitoring model of the cultivation room;

[0114] The data processing unit is used to convert the Tremella cultivation images collected at different monitoring points into simulated growth results corresponding to the three-dimensional cultivation environment monitoring model.

[0115] Specifically, the image processing unit is used to establish three-dimensional coordinates and build a three-dimensional model of the cultivation room in the three-dimensional coordinates according to the dimensions of the cultivation room. In addition, the image processing unit is also used to mark the Tremella fuciformis cultivation images collected at different monitoring points in the three-dimensional model according to the location of the monitoring points.

[0116] The marking unit marks the position of each monitoring point in the three-dimensional model according to the actual position of each monitoring point in the cultivation room. In the three-dimensional model, a three-dimensional grid is formed according to the x-axis, y-axis, and z-axis directions of the three-dimensional coordinates and the distribution of the planting points, and the monitoring data collected by different monitoring points are marked in the three-dimensional grid corresponding to the different planting points. For example, the coordinate position of monitoring point A is (x A ,y A,0), the data collected at monitoring point A include: temperature (collection height is ), upper air humidity (collection height is ), mid-level air humidity (collection height is ), bottom soil moisture (collection height is 0), light intensity (collection height is ) and carbon dioxide concentration (collected at an altitude of ), then the coordinates of temperature correspond to The coordinates of the upper air humidity correspond to The coordinates of the middle-level air humidity correspond to The coordinates of the bottom soil moisture correspond to (x A ,y A ,0), the coordinates of the illumination correspond to The coordinates of carbon dioxide concentration correspond to According to the coordinates of each monitoring point and the coordinates of each planting point, the distance from each monitoring point to the planting point can be calculated.

[0117] The spatial simulation unit is used to form simulated monitoring data in a three-dimensional grid of unlabeled monitoring data according to the set distribution rules of various types of monitoring parameters and the marked monitoring data, so as to form a three-dimensional cultivation environment monitoring model of the cultivation room.

[0118] The simulated monitoring data of each planting point is calculated based on the monitoring data collected by the monitoring points near the planting point. The specific calculation process is as follows:

[0119] Get the distance data between the i-th planting point and each monitoring point, and form an ascending set of distances of monitoring points for the i-th planting point:

[0120] Y i =sort{L i1 ,…,L im ,…,L iM};

[0121] Among them, Y i is the distance ascending set of the i-th planting point, L im is the distance between the mth monitoring point and the ith planting point; 1≤m≤M, M is the number of monitoring points; 1≤i≤I, I is the number of planting points;

[0122] From the distance ascending set of the i-th planting point, select the top three monitoring points as the reference point set:

[0123] A i ={D i1 , D i2 ,D i3};

[0124] Among them, Ai is the reference point set of the i-th planting point, D i1 is the monitoring point closest to the i-th planting point, D i2 is the second closest monitoring point to the i-th planting point, D i3 is the third closest monitoring point to the i-th planting point;

[0125] Based on the monitoring data collected by the top three monitoring points, the simulated monitoring temperature, simulated monitoring humidity, simulated monitoring soil moisture content, simulated monitoring light intensity and simulated monitoring carbon dioxide concentration of the i-th planting point are calculated:

[0126]

[0127] Among them, t i is the simulated monitoring temperature of the i-th planting point, Monitoring point D i1 The collected temperature, δ1 is the first temperature influencing factor; Monitoring point D i2 The collected temperature, δ2 is the second temperature influencing factor; Monitoring point D i3 The collected temperature, δ3 is the third temperature influencing factor; δ1+δ2+δ3=1, δ1>δ2>δ3>0; Δt i is the temperature correction parameter of the i-th planting point;

[0128]

[0129] Among them, r i is the simulated monitoring humidity of the i-th planting point, Monitoring point D i1 The humidity is collected by the humidity sensor closest to the i-th planting point, and λ1 is the first humidity influencing factor; Monitoring point D i1 The humidity collected by the humidity sensor that is second closest to the i-th planting point, λ2 is the second humidity influencing factor; Monitoring point D i2 The humidity collected by the humidity sensor closest to the i-th planting point, λ3 is the third humidity influencing factor; λ1+λ2+λ3=1, λ1>λ2>λ3>0; Δr i is the humidity correction parameter of the i-th planting point;

[0130]

[0131] Among them, b i is the simulated monitored soil moisture content of the i-th planting point; α1 is the first moisture content influencing factor, Monitoring point D i1The collected soil moisture content, α2 is the second moisture content influencing factor, Monitoring point D i2 The collected soil moisture content, α3 is the third moisture content influencing factor, Monitoring point D i3 The collected soil moisture content; α1+α2+α3=1, α1>α2>α3>0; Δb i is the moisture content correction parameter of the i-th planting point;

[0132]

[0133] Among them, c i is the simulated monitoring light intensity of the i-th planting point; β1 is the first light intensity influencing factor, Monitoring point D i1 The collected illuminance, β2 is the second illuminance influencing factor, Monitoring point D i2 The collected illuminance, β3 is the third illuminance influencing factor, Monitoring point D i3 Collected illuminance; β1+β2+β3=1, β1>β2>β3, Δc i Set the corrected illumination for the i-th planting point;

[0134]

[0135] Among them, e i The simulated monitored carbon dioxide concentration for the i-th planting site, Monitoring point D i1 The collected carbon dioxide concentration, θ1 is the first carbon dioxide concentration influencing factor; Monitoring point D i2 The collected carbon dioxide concentration, θ2 is the second carbon dioxide concentration influencing factor; Monitoring point D i3 The collected carbon dioxide concentration, θ3 is the third carbon dioxide concentration influencing factor; θ1+θ2+θ3=1, θ1>θ2>θ3, Δe i is the CO2 concentration correction parameter for the i-th planting site.

[0136] It should be noted that monitoring point D i1 There are two humidity sensors, namely the upper air humidity sensor and the middle air humidity sensor, so the monitoring point D i1 The humidity sensor closest to the i-th planting point and the monitoring point D i1 The second closest humidity sensor to the i-th planting point can be determined by comparing the distances between the two humidity sensors and the i-th planting point. i2The humidity sensor closest to the i-th planting point and the monitoring point D i2 The humidity sensor that is second closest to the i-th planting point can also be determined based on the comparison of the distances between the two humidity sensors and the i-th planting point.

[0137] In this embodiment, the correction parameters for the temperature, humidity, and carbon dioxide concentration at the i-th planting point can be set as needed or taken to be 0. The soil moisture content at the i-th planting point not only takes into account the data collected by the surrounding monitoring points, but also the effects of the surrounding irrigation units. This is corrected by setting a moisture content correction parameter. For example, if the irrigation time of the surrounding cultivation equipment is short and the irrigation range is far from the i-th planting point, the moisture content correction parameter can be a negative number. If the irrigation time of the surrounding cultivation equipment is long and the irrigation range is close to the i-th planting point, the moisture content correction parameter can be a positive number. Furthermore, the illumination at the i-th planting point not only takes into account the data collected by the surrounding monitoring points, but also the light obstruction. The illumination at the i-th planting point is corrected by setting a correction that reflects the light obstruction.

[0138] If the temperature exceeds the range, the temperature adjustment unit can be activated for regulation; if the light intensity does not meet the setting, it can be adjusted through the light unit; if the carbon dioxide concentration is too high, the ventilation unit can be activated to reduce it; the spray unit is used to adjust the humidity, and the spray unit's spray angle is adjustable. The irrigation unit is mainly used to irrigate the soil in the cultivation room. The benefit of irrigation is that when using logs to cultivate Tremella fuciformis, the high moisture content of the soil when the logs are inserted into the soil helps the logs absorb water and maintain a moist growth environment at the planting point on the logs. If the cultivation room does not use log cultivation, the data collection function of the soil moisture sensor can also be turned off, and the irrigation unit can also be turned off.

[0139] Preferably, the Tremella fuciformis is planted at equal distances in the horizontal direction and in the vertical direction at each planting point in the cultivation room; the data processing unit comprises: an image segmentation subunit, a size analysis subunit and a size simulation subunit;

[0140] The image segmentation subunit is used to segment the Tremella cultivation image collected at each monitoring point into longitudinal space and transverse space according to the set segmentation requirements to form a segmented image corresponding to each planting point;

[0141] The size analysis subunit is used to analyze and calculate the size of the Tremella fuciformis in each segmented image;

[0142] The size simulation subunit is used to simulate the Tremella size corresponding to each segmented image into the three-dimensional cultivation environment monitoring model.

[0143] Specifically, the image acquisition modules of each monitoring module group are used to collect Tremella cultivation images at all locations in the cultivation room.

[0144] Because each planting site is equally spaced horizontally and vertically, the image segmentation subunit is used to identify and segment the Tremella fuciformis cultivation image corresponding to each planting site. The size analysis subunit is used to compare the Tremella fuciformis size in each segmented image to calculate the Tremella fuciformis size at each planting site.

[0145] The size simulation subunit is used to simulate the Tremella size corresponding to each segmented image into the three-dimensional cultivation environment monitoring model, that is, to simulate the Tremella size at the corresponding position point of each planting point in the three-dimensional cultivation environment.

[0146] Therefore, the three-dimensional cultivation environment monitoring model not only reflects the monitoring data information, but also reflects the simulation of the size of Tremella fuciformis, and very intuitively reflects the growth of Tremella fuciformis under different monitoring data conditions.

[0147] Preferably, the cloud platform further includes a statistical unit: the statistical unit is used to:

[0148] According to the simulated growth results of the Tremella fuciformis size in the three-dimensional cultivation environment monitoring model, the growth results of the reference Tremella fuciformis size are compared, and the planting points corresponding to the simulated growth results exceeding the first preset value of the reference Tremella fuciformis size are regarded as the growth advantage points, and the planting points corresponding to the simulated growth results less than the second preset value of the reference Tremella fuciformis size are regarded as the growth disadvantage points;

[0149] According to the growth advantage points and growth disadvantage points simulated in the three-dimensional cultivation environment monitoring model, a distribution map of the growth advantage points and growth disadvantage points in the cultivation room is formed.

[0150] Specifically, the reference Tremella size is used to measure the reference growth results of Tremella. It is easy to understand that different reference Tremella sizes are required at different stages of Tremella cultivation. Among them, the reference Tremella size at a certain period can be determined based on the average Tremella size of each planting site in the current period.

[0151] It is easy to understand that the first preset value and the second preset value are positive numbers respectively.

[0152] The growth advantage point is the planting point where the Tremella fuciformis growth size is larger than the average, and the growth disadvantage point is the planting point where the Tremella fuciformis growth size is smaller than the average.

[0153] The distribution map of growth advantage points and growth disadvantage points is used to show which positions of Tremella fuciformis grow well and which positions grow poorly in the entire cultivation room, so that the staff can adjust the growth environment parameters of the disadvantageous points, or appropriately increase the planting point density of the growth advantage points to fully utilize the growth advantage conditions of the growth advantage points.

[0154] Preferably, the cloud platform further comprises a data collection unit and a difference analysis unit;

[0155] The data collection unit is used to arrange the monitoring data of each growth advantage point into a first array, and the monitoring data of all growth advantage points are arranged into a first data set; and is used to arrange the monitoring data of each growth disadvantage point into a second array, and the monitoring data of all growth disadvantage points are arranged into a second data set, wherein each first array and each second array respectively include simulated monitoring temperature, simulated monitoring humidity, simulated monitoring soil moisture content, simulated monitoring light intensity and simulated monitoring carbon dioxide concentration;

[0156] The difference analysis unit is used for:

[0157] Analyze the data types with consistency and the data types with differences in each first array of the first data set; regard the data types with consistency as high-interference data types, and regard the data types with differences as low-interference data types;

[0158] Determining whether the monitoring data corresponding to the high-interference data type in the second array is within a set first standard range;

[0159] If the first standard interval is exceeded, the cultivation equipment of the corresponding planting points of the second array is activated (the effective range of the cultivation equipment covers the corresponding planting points of the second array), so as to adjust the monitoring data of the high-interference data type to the set first standard interval through the cultivation equipment of the corresponding planting points of the second array;

[0160] If it is in the first standard range, determine whether the monitoring data of the corresponding low-interference data type in the second array is in the set second standard range;

[0161] If the second standard interval is exceeded, the cultivation equipment of the second array of corresponding planting points is started to adjust the monitoring data of the low-interference data type to the set second standard interval through the cultivation equipment of the second array of corresponding planting points;

[0162] If it is in the second standard range, mark the second array and mark the planting point corresponding to the second array as an abnormal planting point.

[0163] The first array of monitoring data of the j-th growth advantage point is arranged as follows:

[0164] (t 1j ,r 1j ,b 1j ,c 1j ,e 1j );

[0165] Where, 0≤j≤J≤I, j is the serial number of the growth advantage point, J is the number of growth advantage points; t 1j is the simulated monitoring temperature of the jth growth advantage point, r1j is the simulated monitoring humidity of the jth growth advantage point, b 1j is the simulated monitoring soil moisture content of the jth growth advantage point, c 1j is the simulated monitoring illumination of the jth growth advantage point, e 1j Simulated monitoring of CO2 concentration for the jth growth advantage site;

[0166] The first data set is:

[0167]

[0168] The second array formed by the monitoring data of the k-th growth disadvantage point is:

[0169] (t 2k ,r 2k ,b 2k ,c 2k ,e 2k );

[0170] Where, 0≤k≤K≤I, k is the serial number of the growth disadvantage point, K is the number of growth disadvantage points; t 2k is the simulated monitoring temperature of the kth growth disadvantage point, r 2k is the simulated monitoring humidity of the kth growth disadvantage point, b 2k is the simulated monitoring soil moisture content of the kth growth disadvantage point, c 2k is the simulated monitoring illumination of the kth growth disadvantage point, e 2k Simulated monitoring of CO2 concentration for the kth growth disadvantage site;

[0171] The second data set is:

[0172]

[0173] The consistency of data of one data type in each first array requires the following conditions to be met:

[0174]

[0175]

[0176] Where X is taken from {t, r, b, c, e}, A1 is the first reference value, A1>0;

[0177] For example, when X is t, if the above formula holds, it means that the temperature of the dominant growth point meets the consistency requirement; therefore, the temperature is a high-interference data type;

[0178] If the data of a data type in each first array is different, the following conditions must be met:

[0179]

[0180] Wherein, A2 is the second reference value, A2>A1.

[0181] For example, when X is c, if the above formula is established, it means that the illumination of the dominant growth point meets the difference requirement, so the illumination is a low-interference data type;

[0182] When the temperature is a high-interference data type, determining whether the monitoring data corresponding to the high-interference data type in the second array (i.e., the temperature) is within a set first standard range (e.g., 15 degrees Celsius to 25 degrees Celsius);

[0183] If it exceeds, start the cultivation equipment (i.e., temperature adjustment unit) of the second array corresponding to the planting point to adjust the monitoring data of the high interference data type to the set first standard range through the cultivation equipment (i.e., temperature adjustment unit) of the second array corresponding to the planting point.

[0184] If it is in the set first standard range, then determine whether the monitoring data (illuminance) corresponding to the low-interference data type in the second array is in the set second standard range;

[0185] If it exceeds (for example, the brightness is insufficient), start the cultivation equipment of the second array corresponding to the planting point, so as to adjust the monitoring data of the low-interference data type to the set second standard range (brightness) through the cultivation equipment (i.e., lighting unit) of the second array corresponding to the planting point.

[0186] If it is in the set second standard range (appropriate brightness), mark this second array and mark the planting point corresponding to the second array as an abnormal planting point. At this time, the abnormal planting point may be poor inoculation or other poor growth caused by environmental conditions.

[0187] Preferably, the cloud platform further includes an analysis unit, which is used to:

[0188] Obtaining changes in the growth advantage point area with the acquisition frequency, and obtaining changes in the growth disadvantage point area with the acquisition frequency; wherein the growth disadvantage point will adjust the environmental data through the cultivation equipment;

[0189] Obtain the overlapping areas of growth disadvantage points under different acquisition frequencies;

[0190] Sending the overlapping area to a display module for display;

[0191] Obtain the overlapping areas under different planting round numbers and compare the overlapping ranges of the overlapping areas.

[0192] The control module controls the monitoring module to collect monitoring data according to the set collection frequency and sends it to the cloud platform to understand the monitoring data of each monitoring point under each collection frequency, and promptly discover whether the Tremella fuciformis growth environment data meets the set indicators; and the cloud platform does not necessarily need to determine the growth advantage points and growth disadvantage points from each planting point in each collection cycle. It can distinguish the growth advantage points and growth disadvantage points at intervals of a set number of collection cycles. This is because the Tremella fuciformis growth situation may not necessarily change significantly when the collection frequencies are adjacent.

[0193] Since the growth disadvantage points will adjust the environmental data through the cultivation equipment, the overlapping areas of the growth disadvantage point areas under different collection frequency changes represent areas where the effect of adjusting the environmental data on the growth of Tremella fuciformis is not obvious. At this time, these overlapping areas may be blind spots of the cultivation equipment, or areas where Tremella fuciformis is poorly inoculated. In different Tremella fuciformis planting rounds, if the overlapping areas of each round still overlap, the overlapping range of the overlapping areas is the blind spot of the cultivation equipment. At this time, the blind spot can be marked in the three-dimensional model of the cultivation room so that the next time Tremella fuciformis is selected for planting, the blind spot can be avoided.

[0194] Preferably, the analysis unit is further used for:

[0195] In the planting area, the first area is obtained by taking the union of the areas of each growth disadvantage point;

[0196] Performing a difference operation between the first area and the overlapping range to obtain the inferior area;

[0197] The disadvantageous area is sent to the display module for display.

[0198] Furthermore, the first region obtained by taking the union of each growth disadvantage point region represents the region where Tremella fuciformis is prone to poor growth.

[0199] The first area is subtracted from the overlapping range, and the disadvantageous area obtained excludes the blind spots of the cultivation equipment and the areas where adjusting the environmental parameters cannot improve the growth of Tremella fuciformis. Therefore, the disadvantageous area represents the areas where Tremella fuciformis is prone to poor growth, but the growth environment data of these areas can be improved through cultivation equipment.

[0200] Sending the disadvantageous areas to the display module helps to remind the user that these disadvantageous areas are prone to poor growth of Tremella fuciformis, so that the user can pay attention to and improve the cultivation growth environment data in advance.

[0201] Preferably, the analysis unit is further used for:

[0202] Get the number of the first planting points within the overlapping range;

[0203] The dominant area within the preset radius of the overlapping range is taken as the target area, and the number of second planting points in the target area is obtained;

[0204] Calculate the planting density of the target area after merging the number of first planting points within the overlapping range into the target area;

[0205] When the planting density does not exceed the set density, an adjusted distribution map of each planting point in the target area is obtained according to the sum of the number of the first planting points and the number of the second planting points;

[0206] The adjustment distribution graph is sent to the display module for display.

[0207] Since Tremella fuciformis is planted at equal distances horizontally and vertically at various planting points in the cultivation room, after the overlapping range is determined, the number of the first planting points within the range is determined. In a nearest manner, the planting points corresponding to the number of the first planting points in the overlapping range are tried to be merged into the target area. After the merger, the planting density of the target area is calculated. If the density does not exceed the standard, all the planting points in the overlapping range can be transferred to the target area; if the density exceeds the standard, part of the planting points in the overlapping range will be transferred to the target area, and the part of the planting points with excessive density will be transferred to other advantageous areas.

[0208] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. All equivalent structural transformations made based on the contents of the present invention's description and drawings, or direct / indirect applications in other related technical fields, are included in the patent protection scope of the present invention.

Claims

1. An intelligent cultivation room for Tremella fuciformis cultivation, characterized in that: The cultivation room is provided with a control module and a display module, a plurality of monitoring module groups and a plurality of cultivation devices respectively connected to the control module in communication; the control module is connected to the cloud platform in communication; Each monitoring module group includes a temperature sensor, an upper layer air humidity sensor, a middle layer air humidity sensor, a soil moisture sensor, a light intensity sensor, an image acquisition module and a carbon dioxide sensor; the various planting points in the cultivation room are distributed in a dot matrix form, and the monitoring module groups are distributed at different monitoring points in the cultivation room; The cultivation equipment includes a temperature regulating unit, a lighting unit, a ventilation unit, a spray unit and an irrigation unit; the cultivation equipment is distributed in different cultivation areas of the cultivation room according to the effective range; wherein, each cultivation area is provided with multiple planting points; The control module is used to control the monitoring module group to start according to the set collection frequency, so as to collect monitoring data and send it to the cloud platform. The cloud platform determines the growth advantage points and growth disadvantage points from each planting point based on the image data collected by the image collection module, and forms a distribution map of the growth advantage points and growth disadvantage points in the cultivation room; the cloud platform is also used to calculate the advantageous environment data based on the growth advantage points, and calculate the disadvantageous environment data based on the growth disadvantage points; The control module is further configured to receive the distribution diagram of advantageous and disadvantageous growth points, advantageous environmental data, and disadvantageous environmental data sent by the cloud platform, for display on the display module, and control the cultivation equipment according to the advantageous environmental data to adjust the environmental data of the disadvantageous growth points; The cloud platform also includes an analysis unit, which is used to: obtain changes in the growth advantage point area with the acquisition frequency, and obtain changes in the growth disadvantage point area with the acquisition frequency; wherein the growth disadvantage point will adjust the environmental data through the cultivation equipment; obtain the overlapping area of ​​the growth disadvantage point area under different acquisition frequency changes; send the overlapping area to the display module for display; obtain the overlapping area under different planting round numbers, and compare the overlapping range of the overlapping area; The analysis unit is further configured to: obtain a first region by obtaining a union of each inferior growth point region in the planting region; perform a difference operation between the first region and the overlapped range to obtain an inferior region; and send the inferior region to the display module for display; The analysis unit is also used to: obtain the number of first planting points within the overlapping range; take the dominant area within a preset radius of the overlapping range as the target area, and obtain the number of second planting points in the target area; calculate the planting density of the target area after merging the number of first planting points in the overlapping range into the target area; when the planting density does not exceed the set density, obtain an adjusted distribution map of each planting point arranged in the target area according to the sum of the number of first planting points and the number of second planting points; and send the adjusted distribution map to the display module for display.

2. The intelligent cultivation room for Tremella fuciformis cultivation according to claim 1, characterized in that, The cloud platform includes an image processing unit, a marking unit, a space simulation unit and a data processing unit; The image processing unit is used to form a three-dimensional model of the cultivation room and mark the Tremella cultivation images collected from different monitoring points in the three-dimensional model; The marking unit is used to mark the monitoring data collected from different monitoring points in a three-dimensional grid, so that the monitoring data of different monitoring points are marked in different grid points of the three-dimensional grid of the three-dimensional model; The space simulation unit is used to simulate and distribute the monitoring data marked by the three-dimensional grid into the three-dimensional space of the three-dimensional model to form a three-dimensional cultivation environment monitoring model of the cultivation room; The data processing unit is used to convert the Tremella cultivation images collected at different monitoring points into simulated growth results corresponding to the three-dimensional cultivation environment monitoring model.

3. The intelligent cultivation room for Tremella fuciformis cultivation according to claim 2, characterized in that, Tremella fuciformis is planted at equal distances in the horizontal direction and in the vertical direction at each planting point in the cultivation room; the data processing unit includes: an image segmentation subunit, a size analysis subunit and a size simulation subunit; The image segmentation subunit is used to segment the Tremella cultivation image collected at each monitoring point into longitudinal space and transverse space according to the set segmentation requirements to form a segmented image corresponding to each planting point; The size analysis subunit is used to analyze and calculate the size of the Tremella fuciformis in each segmented image; The size simulation subunit is used to simulate the Tremella size corresponding to each segmented image into the three-dimensional cultivation environment monitoring model.

4. The intelligent cultivation room for Tremella fuciformis cultivation according to claim 3, characterized in that: The cloud platform further includes a statistical unit: the statistical unit is used to: According to the simulated growth results of the Tremella fuciformis size in the three-dimensional cultivation environment monitoring model, the growth results of the reference Tremella fuciformis size are compared, and the planting points corresponding to the simulated growth results exceeding the first preset value of the reference Tremella fuciformis size are regarded as the growth advantage points, and the planting points corresponding to the simulated growth results less than the second preset value of the reference Tremella fuciformis size are regarded as the growth disadvantage points; According to the growth advantage points and growth disadvantage points simulated in the three-dimensional cultivation environment monitoring model, a distribution map of the growth advantage points and growth disadvantage points in the cultivation room is formed.

5. The intelligent cultivation room for Tremella fuciformis cultivation according to claim 4, characterized in that, The cloud platform also includes a data collection unit and a difference analysis unit; The data collection unit is used to arrange the monitoring data of each growth advantage point into a first array, and the monitoring data of all growth advantage points are arranged into a first data set; and is used to arrange the monitoring data of each growth disadvantage point into a second array, and the monitoring data of all growth disadvantage points are arranged into a second data set, wherein each first array and each second array respectively include simulated monitoring temperature, simulated monitoring humidity, simulated monitoring soil moisture content, simulated monitoring light intensity and simulated monitoring carbon dioxide concentration; The difference analysis unit is used for: Analyze the data types with consistency and the data types with differences in each first array of the first data set; regard the data types with consistency as high-interference data types, and regard the data types with differences as low-interference data types; Determining whether the monitoring data corresponding to the high-interference data type in the second array is within a set first standard range; If the first standard interval is exceeded, the cultivation equipment of the corresponding planting points of the second array is started to adjust the monitoring data of the high-interference data type to the set first standard interval through the cultivation equipment of the corresponding planting points of the second array; If it is in the first standard range, determining whether the monitoring data of the corresponding low-interference data type in the second array is in the set second standard range; If the second standard interval is exceeded, the cultivation equipment of the second array of corresponding planting points is started to adjust the monitoring data of the low-interference data type to the set second standard interval through the cultivation equipment of the second array of corresponding planting points; If it is in the second standard range, mark the second array and mark the planting point corresponding to the second array as an abnormal planting point.

6. The intelligent cultivation room for Tremella fuciformis cultivation according to claim 1, characterized in that: The simulated monitoring data of each planting point is calculated based on the monitoring data collected by the monitoring points near the planting point. The specific calculation process is as follows: Get the The distance data between each planting point and each monitoring point is The planting points form a set of monitoring points in ascending order of distance: ； in, For the The distances of the planting points are in ascending order. For the The distance between the monitoring points The distance between planting sites; , is the number of monitoring points; , is the number of planting sites; From From the ascending distance set of planting points, the top three monitoring points are selected as the reference point set: ； in, For the A reference point set of planting sites, For distance The nearest monitoring point to the planting site, For distance The second closest monitoring point to the planting site, For distance The third closest monitoring point to the planting site; According to the monitoring data collected by the top three monitoring points, calculate the Simulated monitoring of temperature, humidity, soil moisture, light intensity and carbon dioxide concentration at each planting point: ； in, For the Simulated monitoring temperature of each planting site, For monitoring points The collected temperature, is the first temperature influencing factor; For monitoring points The collected temperature, is the second temperature influencing factor; For monitoring points The collected temperature, is the third temperature influencing factor; , ; For the Temperature correction parameters for each planting point; ； in, For the Simulated monitoring humidity at each planting site, For monitoring points Middle distance The humidity collected by the humidity sensor closest to each planting point, is the first humidity influencing factor; For monitoring points Middle distance The humidity collected by the humidity sensor closest to the planting point, is the second humidity influencing factor; For monitoring points Middle distance The humidity collected by the humidity sensor closest to each planting point, is the third humidity influencing factor; , ; For the Humidity correction parameters for each planting point; ； in, For the Simulated monitoring of soil moisture at each planting site; is the first moisture content influencing factor, For monitoring points The soil moisture content collected, is the second moisture content influencing factor, For monitoring points The soil moisture content collected, is the third moisture content influencing factor, For monitoring points The moisture content of the collected soil; , ; For the Moisture content correction parameters for each planting point; ； in, For the Simulated monitoring light intensity at each planting point; is the first illumination influencing factor, For monitoring points The collected illuminance, is the second illumination influencing factor, For monitoring points The collected illuminance, is the third illumination influencing factor, For monitoring points The collected illuminance; , , For the Correct the illumination of each planting point; ； in, For the Simulated monitoring of carbon dioxide concentration at each planting site, For monitoring points The collected carbon dioxide concentration, is the first carbon dioxide concentration influencing factor; For monitoring points The collected carbon dioxide concentration, is the second carbon dioxide concentration influencing factor; For monitoring points The collected carbon dioxide concentration, is the third carbon dioxide concentration influencing factor; , , For the CO2 concentration correction parameters for each planting site.

7. The intelligent cultivation room for Tremella fuciformis cultivation according to claim 5, characterized in that: The first array of monitoring data of the j-th growth advantage point is arranged as follows: ； in, , is the number of the growth advantage point, is the number of growth advantage points; For the Simulated monitoring temperature of each growth advantage point, For the Simulated monitoring humidity at each growth advantage point, For the Simulation monitoring of soil moisture at each growth advantage point, For the Simulated monitoring light intensity at each growth advantage point, For the Simulated monitoring of carbon dioxide concentration at each growth advantage point; is the number of planting sites; The first data set is: ； No. The second array formed by arranging the monitoring data of the growth disadvantage points is: ； in, , is the serial number of the growth disadvantage point, is the number of growth disadvantage points; For the Simulated monitoring temperature of the growth disadvantage point, For the Simulated monitoring humidity of the growth disadvantage point, For the Simulation monitoring of soil moisture content at each growth disadvantage point, For the Simulated monitoring light intensity of the growth disadvantage point, For the Simulated monitoring of carbon dioxide concentration at each growth disadvantage point; The second data set is: ； The consistency of data of one data type in each first array requires the following conditions to be met: ； in, from The value in is the first reference value, ; If the data of a data type in each first array is different, the following conditions must be met: ； in, is the second reference value, .

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