CN118131844A - Animal greenhouse management system based on internet of things data identification - Google Patents
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Abstract
The invention relates to the technical field of greenhouse management, and discloses an animal greenhouse management system based on data identification of the Internet of things, which comprises an ecological health analysis module, a greenhouse environment monitoring module, a greenhouse environment optimization module and a user interface; the ecological health analysis module is responsible for collecting various parameters of reptiles of the snake order and constructing an animal ecological health assessment model; the greenhouse environment monitoring module monitors the indoor environment parameters in real time through the environment monitoring sensor and transmits the data to the greenhouse environment optimizing module; the greenhouse environment optimization module utilizes the collected parameters, determines the most suitable environment parameter combination through a genetic algorithm, and automatically adjusts greenhouse conditions to maintain the parameters; the user interface allows the user to view all monitoring data and health evaluation results in real time, and simultaneously supports manual adjustment of environmental parameters, so that accurate matching and dynamic adjustment of the environmental parameters are realized, and the requirements of animal health change are met.
Description
Technical Field
The invention relates to the technical field of greenhouse management, in particular to an animal greenhouse management system based on data identification of the Internet of things.
Background
In modern agriculture and animal breeding industry, development and application of intelligent greenhouse management systems have become one of key technologies for improving animal breeding efficiency and animal welfare. In the breeding process of special living things such as reptiles of the order snake, accurate environmental control is critical to the growth and health of the living things, the animals are extremely sensitive to environmental factors such as temperature, humidity, illumination and the like, and small changes of the environmental parameters can have great influence on the animals. There are many kinds of greenhouse management systems on the market, and these systems mainly rely on traditional sensor technology to monitor the environmental conditions in the greenhouse, and these systems can monitor environmental parameters in real time and automatically adjust the environment in the greenhouse according to preset standards to maintain proper cultivation conditions.
These existing systems generally have some technical limitations. First, most systems employ a static environmental control strategy, which means that once environmental parameters are set, the system will continuously maintain these parameters regardless of the animal's growth needs over time or the internal regulatory needs imposed by changes in the external environment, which may lead to a mismatch between the indoor environment and the actual needs of the animal. Second, the data processing and analysis capabilities in current systems are relatively limited. Although a large amount of environmental data can be collected, the comprehensive analysis and utilization of the data is not high, and the potential of the data in animal health monitoring and environmental management cannot be fully utilized. In general, while existing animal greenhouse management systems provide basic environmental control functions for animal farming, their ability to adapt to dynamic environments and to comprehensively utilize data remains to be improved. These technical deficiencies limit the overall effectiveness of the system and may affect the health and growth of the animal. In order to solve the above problems, a technical solution is now provided.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides the animal greenhouse management system based on the data identification of the Internet of things, and the animal greenhouse management system is characterized in that a model is built by integrating an ecological health analysis module, a greenhouse environment monitoring module, a greenhouse environment optimization module and a user interface, and a genetic algorithm is utilized to realize the accurate matching and dynamic adjustment of environmental parameters, so that the problem that the environmental parameters cannot be dynamically adjusted according to the ecological health condition of animals in the prior art is solved, and the growth conditions of reptiles of snakes are optimized.
In order to achieve the above purpose, the present invention provides the following technical solutions:
an animal greenhouse management system based on data identification of the Internet of things comprises an ecological health analysis module, a greenhouse environment monitoring module, a greenhouse environment optimization module and a user interface, wherein the ecological health analysis module is connected with the greenhouse environment optimization module, the greenhouse environment monitoring module is connected with the greenhouse environment optimization module, the user interface is respectively connected with the ecological health analysis module, the greenhouse environment monitoring module and the greenhouse environment optimization module, the ecological health analysis module is used for collecting and analyzing the behavior parameters, the physiological parameters, the neural activity parameters and the digestion parameters of reptiles of the snake order, comprehensively evaluating the ecological health state of the reptiles of the snake order, comprises an ecological health parameter collecting unit, a behavior health index evaluating unit, a physiological health index evaluating unit and an ecological health evaluating unit, the ecological health parameter acquisition unit is respectively connected with the behavior health index evaluation unit, the physiological health index evaluation unit and the ecological health evaluation unit, the behavior health index evaluation unit is connected with the ecological health evaluation unit, the physiological health index evaluation unit is connected with the ecological health evaluation unit, and the ecological health evaluation unit constructs an animal ecological health evaluation model according to the parameters acquired by the ecological health parameter acquisition unit, the behavior health index acquired by the behavior health index evaluation unit and the physiological health index acquired by the physiological health index evaluation unit, so as to acquire an animal ecological health evaluation value, wherein the formula of the animal ecological health evaluation model is as follows:
; wherein H is an animal ecological health evaluation value, BHI is a behavioral health index, LHI is a biological health index, PV is a biological signal average voltage value, FV is a biological signal peak frequency, and EA is a digestive enzyme activity value;
The greenhouse environment optimization module comprises an environment parameter analysis unit, an environment parameter optimization unit and an environment parameter adjustment unit, wherein the environment parameter analysis unit is connected with the environment parameter optimization unit, and the environment parameter optimization unit is connected with the environment parameter adjustment unit.
As a further scheme of the invention, the ecological health parameter acquisition unit continuously records and analyzes bioelectric signals of the reptile of the snake order by a neuroelectrophysiological monitoring technology to obtain the neuroactivity parameters of the animal, wherein the neuroactivity parameters comprise the average voltage value of the bioelectric signals and the peak frequency of the bioelectric signals; determining digestive parameters of the reptiles of the order Serpentis, the digestive parameters including digestive enzyme activity values, and transmitting the data to an ecological health assessment unit using a communication technique.
As a further scheme of the invention, the ecological health parameter acquisition unit monitors and analyzes behaviors of the reptile animals in the order of snakes through the high-resolution camera and the image recognition technology to obtain behavior parameters of the animals, wherein the behavior parameters comprise activity frequency, interaction event frequency, certain stay time in a hot zone, total stay time and ultraviolet irradiation time, an ultraviolet irradiation time reference value is preset according to the needs of the reptile animals in the order of snakes, data are transmitted to the behavior health index evaluation unit through the communication technology, and the behavior health index evaluation unit obtains animal behavior health indexes by constructing a behavior health index evaluation model, wherein the formula of the behavior health index evaluation model is as follows:
; wherein BHI is an animal's behavioral health index, AF is an activity frequency, IE is an interaction event frequency, T ' H is a certain hot zone residence time, T H is a total residence time, T UVB is an ultraviolet irradiation time, and T I is an ultraviolet irradiation time reference value.
As a further scheme of the invention, in a formula of the behavioral health index evaluation model, the activity frequency is a count of the number of activities of the reptiles of the Serpentis within a certain time, the interaction event frequency is the number of interactions of the reptiles of the Serpentis with other animals, the total residence time is the total residence time of the reptiles of the Serpentis in all areas, and the ultraviolet irradiation time is the exposure time of the reptiles of the Serpentis within the ultraviolet irradiation range.
As a further scheme of the invention, the ecological health parameter acquisition unit acquires physiological parameters of the reptile of the snake order through the physiological monitor, wherein the physiological parameters comprise body surface temperature, body surface humidity, heart rate, respiratory rate and skin resistance, the data are transmitted to the physiological health index evaluation unit by utilizing a communication technology, the physiological health index evaluation unit constructs a physiological health index evaluation model, and the physiological health index of the animal is acquired, wherein the formula of the physiological health index evaluation model is as follows:
; wherein LHI is the physiological health index of the animal, T b is the body surface temperature, HD is the body surface humidity, HR is the heart rate, R is the respiratory rate, and SC is the skin resistance.
As a further scheme of the invention, the greenhouse environment monitoring module monitors the indoor environment parameters in real time through the environment monitoring sensor based on the data identification of the Internet of things, and transmits the obtained environment parameters to the greenhouse environment optimization module by utilizing a communication technology, wherein the environment parameters comprise the temperature, the humidity, the carbon dioxide concentration, the illumination intensity and the illumination duration in the intelligent greenhouse.
As a further scheme of the invention, the environmental parameter analysis unit utilizes a statistical analysis technology to construct a structural equation model to obtain the influence intensity of environmental parameters on animal ecological health evaluation values through intermediate variables, wherein the step of constructing the structural equation model is as follows:
Step S1, setting environmental parameters as external variables, taking behavior parameters, physiological parameters, nerve activity parameters and digestion parameters of the reptile of the snake order as intermediate variables, taking an animal ecological health evaluation value as a final internal variable, and drawing causal relations from the external variables to the intermediate variables and from the intermediate variables to the internal variables by using a graphic tool;
S2, estimating model parameters by using a maximum likelihood method, ensuring that all variables and paths are defined, and running an estimation process after the model input configuration is completed to obtain coefficients of each path;
S3, checking the generated comparison fitting index and root mean square error approximation after parameter estimation is completed, confirming that the index meets a preset standard, adjusting a path of the model when the index does not meet the standard, and running the estimation process again for verification;
and S4, analyzing and recording the path coefficient of the final model, and utilizing the path coefficient to indicate the influence intensity of the environmental parameter on the animal ecological health evaluation value through the intermediate variable.
As a further aspect of the present invention, the environmental parameter optimizing unit finds a target environmental parameter combination of the reptile of the order snake using a genetic algorithm based on the result obtained by the environmental parameter analyzing unit, wherein the finding of the target environmental parameter combination of the reptile of the order snake includes the steps of:
A1, determining an optimization target of a genetic algorithm to maximize an animal ecological health evaluation value of a reptile of the snake order, setting an fitness function, and evaluating the effect of a given environmental parameter combination by the fitness function based on a path coefficient provided by an environmental parameter analysis unit to obtain a fitness value, wherein the fitness function has the following expression:
; wherein F is the fitness value, p i is the ith parameter of the environmental parameter, m j is the jth parameter of the intermediate variable,/> As the path coefficient, H is the animal ecological health evaluation value,/>Is a weight factor;
a2, coding environmental parameters into individuals in a genetic algorithm, randomly generating an initial population, wherein each individual represents a group of environmental parameter settings, selecting excellent individuals for reproduction by using a roulette selection method, defining crossover and mutation operations, allowing the two individuals to exchange part of genes, and randomly changing part of genes of the individuals by the mutation operations;
Step A3, calculating expected animal ecological health evaluation values under each environment setting by utilizing a formula of an animal ecological health evaluation model based on the states of the path coefficients and the intermediate variables;
Step A4, continuously generating a new population through selection, crossing and mutation operations, evaluating the fitness value of all individuals in each generation, retaining the individuals with the best performance, and terminating the algorithm when the fitness value reaches a set threshold value;
and step A5, selecting an individual with the highest fitness value from the final output of the genetic algorithm, namely the target environment parameter combination of the reptiles of the snake order.
As a further aspect of the present invention, the environmental parameter adjustment unit receives the target environmental parameter combination from the environmental parameter analysis unit, and automatically adjusts the environmental parameter in the greenhouse.
As a further aspect of the invention, the user interface supports the user manually adjusting environmental parameters to meet the growth environmental conditions of the reptiles and allows the user to view real-time and historical data of greenhouse environmental parameters and reptile behavior parameters, physiological parameters, neural activity parameters, and digestive parameters.
Compared with the prior art, the animal greenhouse management system based on the data identification of the Internet of things has the beneficial effects that: according to the invention, various parameters of the reptile of the snake order are collected in real time, a health evaluation model is constructed, the health condition of the animal is accurately evaluated, the overall health state of the animal is determined, the early warning capability of the animal on health problems is improved, and a scientific basis is provided for subsequent environmental adjustment.
Compared with the prior art, the animal greenhouse management system based on the data identification of the Internet of things has the beneficial effects that: according to the environment parameters and animal health evaluation values monitored in real time, the environment setting in the greenhouse is automatically optimized through the genetic algorithm, so that the optimal state of the environment where the animal is located can be ensured, the environment change can be responded flexibly, key parameters such as temperature, humidity and illumination can be adjusted, and the growth and health of the animal can be supported in an optimal mode.
Drawings
Fig. 1 is a schematic structural diagram of an animal greenhouse management system based on internet of things data identification.
Detailed Description
The technical solutions of the present embodiment will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is apparent that the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
An animal greenhouse management system based on data identification of the Internet of things comprises an ecological health analysis module, a greenhouse environment monitoring module, a greenhouse environment optimization module and a user interface.
The ecological health analysis module is used for collecting and analyzing the behavior parameters, the physiological parameters, the neural activity parameters and the digestion parameters of the reptiles of the snake, and comprehensively evaluating the ecological health state of the reptiles of the snake.
The ecological health analysis module comprises an ecological health parameter acquisition unit, wherein the ecological health parameter acquisition unit monitors and analyzes behaviors of the reptiles of the snakes through a high-resolution camera and an image recognition technology to obtain behavior parameters of the animals, the behavior parameters comprise an activity frequency, an interaction event frequency, a certain hot zone residence time, a certain total residence time and an ultraviolet irradiation time, an ultraviolet irradiation time reference value is preset according to the requirements of the reptiles of the snakes, and the behavior parameters are transmitted to a behavior health index evaluation unit through a wireless communication technology; physiological parameters of the reptiles of the snake order are obtained through a physiological monitor, wherein the physiological parameters comprise body surface temperature, body surface humidity, heart rate, respiratory rate and skin resistance, and the physiological parameters are transmitted to a physiological health index evaluation unit by utilizing a wireless communication technology; continuously recording and analyzing bioelectric signals of the reptiles of the snake order by using a neuroelectrophysiological monitoring technology to obtain neuro-activity parameters of the animals, wherein the neuro-activity parameters comprise an average voltage value of the bioelectric signals and a peak frequency of the bioelectric signals; determining digestive parameters of reptiles of the order Serpentis by biochemical analysis technique, wherein the digestive parameters comprise digestive enzyme activity value, and transmitting nerve activity parameters and digestive parameters to the ecological health evaluation module by wireless communication technique.
The ecological health analysis module in the embodiment of the invention comprises a behavior health index evaluation unit, wherein a behavior health index evaluation model is constructed by using the activity frequency, the interaction event frequency, the hot zone residence time, the total residence time, the ultraviolet irradiation time and the ultraviolet irradiation time reference value, and the animal behavior health index is obtained, wherein the formula of the behavior health index evaluation model is as follows:
; wherein BHI is an animal's behavioral health index, AF is an activity frequency, IE is an interaction event frequency, T ' H is a certain hot zone residence time, T H is a total residence time, T UVB is an ultraviolet irradiation time, and T I is an ultraviolet irradiation time reference value.
The ecological health analysis module in the embodiment of the invention comprises a physiological health index evaluation unit, and a physiological health index evaluation model is constructed by using body surface temperature, body surface humidity, heart rate, respiratory rate and skin resistance to obtain an animal physiological health index, wherein the formula of the physiological health index evaluation model is as follows:
; wherein LHI is the physiological health index of the animal, T b is the body surface temperature, HD is the body surface humidity, HR is the heart rate, R is the respiratory rate, and SC is the skin resistance.
The ecological health analysis module in the embodiment of the invention comprises an ecological health assessment unit, wherein the ecological health assessment unit is used for constructing an animal ecological health assessment model according to the acquired parameters to obtain an animal ecological health assessment value, and the formula of the animal ecological health assessment model is as follows:
; h is an animal ecological health evaluation value, BHI is a behavioral health index, LHI is a biological health index, PV is a biological signal average voltage value, FV is a biological signal peak frequency, and EA is a digestive enzyme activity value.
The greenhouse environment monitoring module in the embodiment of the invention monitors the indoor environment parameters in real time through the environment monitoring sensor based on the data identification of the Internet of things, and transmits the obtained environment parameters to the greenhouse environment optimization module by utilizing the communication technology, wherein the environment parameters comprise the indoor temperature, the humidity, the carbon dioxide concentration, the illumination intensity and the illumination duration of the intelligent greenhouse.
The greenhouse environment optimization module is used for constructing a model based on the animal ecological health evaluation value and the environment parameters, obtaining the influence intensity of the environment parameters on the animal ecological health evaluation value through the intermediate variables, determining the target environment parameter combination of the reptiles by utilizing a genetic algorithm, and executing environment parameter adjustment.
The greenhouse environment optimization module in the embodiment of the invention comprises an environment parameter analysis unit, wherein the environment parameter analysis unit obtains the influence intensity of environment parameters on animal ecological health evaluation values through intermediate variables by constructing a structural equation model, and the construction of the structural equation model comprises the following steps:
Step S1, opening LISREL software, selecting a new model option to start to create a new structural equation model in a software interface, setting environmental parameters as external variables, behavior parameters, physiological parameters, neural activity parameters and digestion parameters of the reptiles as intermediate variables in a model editor, setting an animal ecological health assessment value as a final internal variable, setting direct influence of the environmental parameters on the intermediate variables according to previous researches, reflecting how environmental conditions directly change physiological and behavioral states of animals, setting influence of the intermediate variables on the internal variable based on formulas of the existing ecological health analysis model, presetting influence of the intermediate variables on overall health of the animals, and drawing a causal path from the external variables to the intermediate variables and from the intermediate variables to the internal variables by using a path tool;
step S2, opening Jupyter Notebook by using a Python environment;
import Pandas library: input' import pandas;
Loading data: using 'pd.read_csv (' path/file;
Checking and processing missing values: filling the missing values with ' dataframe = ' ffill ';
Data normalization: normalization processing is performed on all numerical data using' from sklearn.preprocessing import StandardScaledataframe _scaled=scaler.fit_ transform (dataframe);
storing the processed data for later use;
step S3, importing the preprocessed data file in LISREL;
Selecting 'maximum likelihood estimation' as a parameter estimation method in model setting;
Assigning an initial estimate of each path in the model to 0.1 to begin iteration;
starting a model estimation process, and waiting LISREL for calculation to be completed;
S4, checking LISREL the model fitting report output by the step;
recording a fitting index, including comparing the fitting index with a root mean square error approximation, and checking whether the fitting index satisfies the comparison fitting index > 0.95, and the root mean square error approximation is < 0.06;
if the fitting index is unsatisfactory, adjusting model parameters or reconfiguring model paths according to the requirement;
step S5, checking LISREL the output path coefficient result;
Recording each path coefficient from the outlier variable to the mediator variable, and from the mediator variable to the internal outlier variable;
the influence intensity of the environmental parameters on the animal ecological health evaluation value through the intermediate variable is indicated by the path coefficient.
The greenhouse environment optimization module in the embodiment of the invention comprises an environment parameter optimization unit, wherein the environment parameter optimization unit searches for the optimal environment parameter combination of the reptiles of the snake order by utilizing a genetic algorithm based on the result obtained by the environment parameter analysis unit, and the searching for the optimal environment parameter combination of the reptiles of the snake order comprises the following steps:
A1, determining an optimization target of a genetic algorithm to maximize an animal ecological health evaluation value of a reptile of the snake order, setting an fitness function, and evaluating the effect of a given environmental parameter combination by the fitness function based on a path coefficient provided by an environmental parameter analysis unit to obtain a fitness value, wherein the fitness function has the following expression:
; wherein F is the fitness value, p i is the ith parameter of the environmental parameter, m j is the jth parameter of the intermediate variable,/> As the path coefficient, H is the animal ecological health evaluation value,/>Is a weight factor;
Step A2, coding environmental parameters into individuals in a genetic algorithm, randomly generating an initial population, wherein each individual represents a group of possible environmental parameter settings, selecting excellent individuals for reproduction by using a roulette selection method, selecting individuals with higher fitness with higher probability for a subsequent reproduction process, and defining crossover and mutation operations, wherein the crossover operations allow the two individuals to exchange a certain part of genes of the individuals, and the mutation operations randomly change a certain gene of the individuals to simulate natural genetic variation;
Step A3, calculating expected animal ecological health evaluation values under each environment setting by utilizing a formula of an animal ecological health evaluation model based on the states of the path coefficients and the intermediate variables;
Step A4, continuously generating a new population through selection, crossing and mutation operations, evaluating the fitness value of all individuals in each generation, retaining the individuals with the best performance, and terminating the algorithm when the fitness value reaches a set threshold value;
And step A5, selecting an individual with the highest fitness value from the final output of the genetic algorithm, namely the optimal environment parameter combination of the reptiles of the snake order.
The following is an example of a Python code, which uses genetic algorithm to determine the optimal environmental parameter combination of the reptile of the order snake, note that this example is only one starting point, and may need to be adjusted according to the actual situation and the device interface in practical application;
import numpy as np
Parameter setting
Population_size=20# population size
Number of genes_count=3# parameters
Generation = number of 10# iterations
# Generation of initial population
population = np.random.rand(population_size, genes_count)
Fitness function #
def fitness(population):
Reduced np. Sum (axis=1) # reduced fitness assessment
# Genetic algorithm Main Loop
for _ in range(generations):
Selection procedure #
fit = fitness(population)
Parents = placement [ np. Argsort (fit) [ -placement_size// 2: ] ] # half-best individuals were selected
Cross and variation #
cross_point = np.random.randint(1, genes_count)
children = np.array([np.concatenate([p[:cross_point], q[cross_point:]])
for p in parents for q in parents if np.random.rand()>0.5])
mutation = np.where(np.random.rand(children.shape[0], genes_count)<0.1,
np.random.rand(children.shape[0], genes_count), children)
population = np.vstack([parents, mutation[:population_size-len(parents)]])
# Output optimal parameters
best_idx = np.argmax(fitness(population))
print("Optimal Parameters:", population[best_idx])
This code is merely exemplary and requires modification and adjustment as appropriate to the particular circumstances in the application.
The greenhouse environment optimization module in the embodiment of the invention comprises an environment parameter adjustment unit, wherein the environment parameter adjustment unit receives the target environment parameter combination of the reptiles from the environment parameter analysis unit and automatically adjusts the environment parameters in the greenhouse.
The user interface in the embodiment of the invention supports the manual adjustment of the environmental parameters by the user to meet the growth environmental conditions of the reptiles of the snake, and allows the user to view real-time and historical data of the greenhouse environmental parameters and the behavior parameters, physiological parameters, neural activity parameters and digestion parameters of the reptiles of the snake.
The ecological health analysis module is connected with the greenhouse environment optimization module, the greenhouse environment monitoring module is connected with the greenhouse environment optimization module, the greenhouse environment optimization module is connected with the user interface, the ecological health analysis module is connected with the user interface, the greenhouse environment monitoring module is connected with the user interface, the ecological health parameter acquisition unit is connected with the behavior health index evaluation unit, the ecological health parameter acquisition unit is connected with the physiological health index evaluation unit, the ecological health parameter acquisition unit is connected with the ecological health evaluation unit, the behavior health index evaluation unit is connected with the ecological health evaluation unit, the physiological health index evaluation unit is connected with the ecological health evaluation unit, the environment parameter analysis unit is connected with the environment parameter optimization unit, and the environment parameter optimization unit is connected with the environment parameter adjustment unit.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The animal greenhouse management system based on the data identification of the Internet of things comprises an ecological health analysis module, a greenhouse environment monitoring module, a greenhouse environment optimization module and a user interface, and is characterized in that the ecological health analysis module is connected with the greenhouse environment optimization module, the greenhouse environment monitoring module is connected with the greenhouse environment optimization module, the user interface is respectively connected with the ecological health analysis module, the greenhouse environment monitoring module and the greenhouse environment optimization module, the ecological health analysis module comprises an ecological health parameter acquisition unit, a behavior health index evaluation unit, a physiological health index evaluation unit and an ecological health evaluation unit, the behavior health index evaluation unit is connected with the ecological health evaluation unit, the physiological health index evaluation unit is connected with the ecological health evaluation unit, and an animal ecological health evaluation model is built by the ecological health evaluation unit according to parameters acquired by the ecological health parameter acquisition unit, the behavior health index acquired by the behavior health index evaluation unit and the physiological health index acquired by the physiological health index evaluation unit, and the animal ecological health evaluation model is obtained, and the animal ecological health evaluation model formula is as follows:
; wherein H is an animal ecological health evaluation value, BHI is a behavioral health index, LHI is a biological health index, PV is a biological signal average voltage value, FV is a biological signal peak frequency, and EA is a digestive enzyme activity value.
2. The animal greenhouse management system based on the internet of things data recognition according to claim 1, wherein the greenhouse environment optimization module comprises an environment parameter analysis unit, an environment parameter optimization unit and an environment parameter adjustment unit, wherein the environment parameter analysis unit is connected with the environment parameter optimization unit, and the environment parameter optimization unit is connected with the environment parameter adjustment unit.
3. The animal greenhouse management system based on the data identification of the internet of things according to claim 1, wherein the ecological health analysis module is used for collecting and analyzing the behavior parameters, the physiological parameters, the neural activity parameters and the digestion parameters of the reptiles of the snake order, and comprehensively evaluating the ecological health state of the reptiles of the snake order; the ecological health parameter acquisition unit is respectively connected with the behavior health index evaluation unit, the physiological health index evaluation unit and the ecological health evaluation unit; the ecological health parameter acquisition unit continuously records and analyzes bioelectric signals of the reptiles of the snake order through a neuroelectrophysiological monitoring technology to obtain neuro-activity parameters of the animals, wherein the neuro-activity parameters comprise a bioelectric signal average voltage value and a bioelectric signal peak frequency; determining digestive parameters of the reptiles of the order Serpentis, the digestive parameters including digestive enzyme activity values, and transmitting the data to an ecological health assessment unit using a communication technique.
4. The animal greenhouse management system based on internet of things data identification according to claim 2, wherein the ecological health parameter acquisition unit monitors and analyzes behaviors of the reptiles by means of a high-resolution camera and an image recognition technology to obtain behavior parameters of the animals, the behavior parameters comprise an activity frequency, an interaction event frequency, a certain hot zone stay time, a total stay time and an ultraviolet irradiation time, and preset ultraviolet irradiation time reference values according to requirements of the reptiles, wherein the activity frequency is a count of the number of activities of the reptiles in a certain time, the interaction event frequency is a count of interactions of the reptiles with other animals, the total stay time is a total stay time of the reptiles in all areas, the ultraviolet irradiation time is an exposure time of the reptiles in an ultraviolet irradiation range, the data are transmitted to the behavior health index evaluation unit by means of a communication technology, and the behavior health index evaluation unit obtains animal behavior health indexes by constructing a behavior health index evaluation model, wherein a formula of the behavior health index evaluation model is as follows:
; wherein BHI is an animal's behavioral health index, AF is an activity frequency, IE is an interaction event frequency, T ' H is a certain hot zone residence time, T H is a total residence time, T UVB is an ultraviolet irradiation time, and T I is an ultraviolet irradiation time reference value.
5. The animal greenhouse management system based on the data identification of the internet of things according to claim 2, wherein the ecological health parameter acquisition unit obtains physiological parameters of the reptile by a physiological monitor, the physiological parameters comprise body surface temperature, body surface humidity, heart rate, respiratory rate and skin resistance, the data are transmitted to the physiological health index assessment unit by using a communication technology, the physiological health index assessment unit constructs a physiological health index assessment model, and an animal physiological health index is obtained, wherein the formula of the physiological health index assessment model is as follows:
; wherein LHI is the physiological health index of the animal, T b is the body surface temperature, HD is the body surface humidity, HR is the heart rate, R is the respiratory rate, and SC is the skin resistance.
6. The animal greenhouse management system based on the internet of things data recognition according to claim 2, wherein the greenhouse environment monitoring module monitors the environmental parameters in the greenhouse in real time through the environment monitoring sensor based on the internet of things data recognition, and transmits the obtained environmental parameters to the greenhouse environment optimization module by using a communication technology, wherein the environmental parameters comprise temperature, humidity, carbon dioxide concentration, illumination intensity and illumination duration in the intelligent greenhouse.
7. The animal greenhouse management system based on the data identification of the internet of things according to claim 2, wherein the environmental parameter analysis unit constructs a structural equation model by using a statistical analysis technology, and obtains the influence intensity of environmental parameters on the animal ecological health assessment value through an intermediate variable, and the step of constructing the structural equation model is as follows:
Step S1, setting environmental parameters as external variables, taking behavior parameters, physiological parameters, nerve activity parameters and digestion parameters of the reptile of the snake order as intermediate variables, taking an animal ecological health evaluation value as a final internal variable, and drawing causal relations from the external variables to the intermediate variables and from the intermediate variables to the internal variables by using a graphic tool;
S2, estimating model parameters by using a maximum likelihood method, ensuring that all variables and paths are defined, and running an estimation process after the model input configuration is completed to obtain coefficients of each path;
S3, checking the generated comparison fitting index and root mean square error approximation after parameter estimation is completed, confirming that the index meets a preset standard, adjusting a path of the model when the index does not meet the standard, and running the estimation process again for verification;
and S4, analyzing and recording the path coefficient of the final model, and utilizing the path coefficient to indicate the influence intensity of the environmental parameter on the animal ecological health evaluation value through the intermediate variable.
8. The animal greenhouse management system based on internet of things data recognition according to claim 2, wherein the environmental parameter optimization unit searches for a target environmental parameter combination of the reptiles of the order snake using a genetic algorithm based on the result obtained by the environmental parameter analysis unit, wherein searching for the target environmental parameter combination of the reptiles of the order snake comprises the steps of:
A1, determining an optimization target of a genetic algorithm to maximize an animal ecological health evaluation value of a reptile of the snake order, setting an fitness function, and evaluating the effect of a given environmental parameter combination by the fitness function based on a path coefficient provided by an environmental parameter analysis unit to obtain a fitness value, wherein the fitness function has the following expression:
; wherein F is the fitness value, p i is the ith parameter of the environmental parameter, m j is the jth parameter of the intermediate variable,/> As the path coefficient, H is the animal ecological health evaluation value,/>Is a weight factor;
a2, coding environmental parameters into individuals in a genetic algorithm, randomly generating an initial population, wherein each individual represents a group of environmental parameter settings, selecting excellent individuals for reproduction by using a roulette selection method, defining crossover and mutation operations, allowing the two individuals to exchange part of genes, and randomly changing part of genes of the individuals by the mutation operations;
Step A3, calculating expected animal ecological health evaluation values under each environment setting by utilizing a formula of an animal ecological health evaluation model based on the states of the path coefficients and the intermediate variables;
Step A4, continuously generating a new population through selection, crossing and mutation operations, evaluating the fitness value of all individuals in each generation, retaining the individuals with the best performance, and terminating the algorithm when the fitness value reaches a set threshold value;
and step A5, selecting an individual with the highest fitness value from the final output of the genetic algorithm, namely the target environment parameter combination of the reptiles of the snake order.
9. The animal greenhouse management system based on the internet of things data identification according to claim 1, wherein the environmental parameter adjustment unit receives the target environmental parameter combination from the environmental parameter analysis unit, and automatically adjusts the environmental parameters in the greenhouse.
10. The animal greenhouse management system based on internet of things data identification of claim 1, wherein the user interface supports a user to manually adjust environmental parameters to meet growth environmental conditions of the reptiles and allows the user to view real-time and historical data of greenhouse environmental parameters and reptile behavior parameters, physiological parameters, neural activity parameters, and digestive parameters.
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