A big data-based method and system for controlling the environment of toad breeding

Abstract

The application discloses a toad breeding environment management and control method and system based on big data, and particularly relates to the technical field of data processing specially used for agricultural breeding, and is used for solving the problem that the existing management and control method can only compromise control in the whole field when multiple growth stages coexist, so that the environment parameters of each stage deviate from the most suitable range; by collecting environment parameters of each breeding area and obtaining growth stage information, the demand non-coexistence interval of the coexisting growth stage set on each environment parameter dimension is determined to mark the conflict breeding area, the deviation amount is calculated, and the adjustment interference degree is determined in combination with the pipeline sharing condition and the spatial adjacency relationship; under the satisfaction of crosstalk constraints, the marginal physiological benefit elasticity ratio is calculated according to the physiological response elasticity and marginal benefit of each growth stage, the inter-stage resource competition order is generated, and the environment adjustment resources are released in sequence and step by step to obtain the control target value, and finally, the control signal is generated to drive the environment adjustment equipment of each conflict breeding area to implement partition control.

Description

Technical Field

[0001] This invention relates to the field of data processing technology specifically for agricultural aquaculture, and more specifically, to a method and system for environmental management and control of toad farming based on big data. Background Technology

[0002] In toad farming, the stable control of environmental parameters such as temperature, humidity, light, and water exchange directly affects the yield of toad venom and the survival rate of the frog population. Currently, large-scale farms generally use sensors to collect environmental data from multiple points within the sheds and use centralized control systems to automatically adjust equipment such as ventilation, misting, shading, and heating. These environmental control methods typically use the optimal environmental range for a single species and a single growth stage as the target, operating according to pre-calibrated parameter curves, or making feedback corrections based on the deviation between real-time monitoring values ​​and set values. When only the same batch of toads exists in the farm, this method can maintain a relatively stable farming environment.

[0003] However, in order to ensure year-round production, in actual production, multiple growth stages such as tadpoles, tadpoles, juvenile frogs, sub-adults, and adult frogs in the venom-collecting period often coexist in different pool areas of the same shed. The environmental factors such as temperature, humidity, water depth, and light duration required by each stage conflict with each other. Existing control methods cannot meet these differentiated requirements simultaneously in the same space. Usually, a compromise value can only be taken across the entire field, which causes the environmental parameters of all growth stages to deviate from their respective optimal ranges, resulting in hindered metamorphosis, reduced disease resistance, and unstable toad venom production per unit. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a method and system for the management and control of toad farming environment based on big data to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for environmental management of toad farming based on big data includes the following steps:

[0007] S1. Collect environmental parameters from multiple breeding areas within the toad breeding shed and obtain information on the current growth stage of toads in each breeding area;

[0008] S2. Based on growth stage information, determine the set of coexisting growth stages. According to the demand range of each growth stage for environmental parameters, determine the incompatible demand range of the set of coexisting growth stages in each environmental parameter dimension. Mark the breeding area where the environmental parameters fall into the incompatible demand range as the conflict breeding area.

[0009] S3. Calculate the deviation between the environmental parameters of each conflicting aquaculture zone and the optimal value of the demand range of its growth stage, and determine the regulation interference degree of each pair of conflicting aquaculture zones based on the sharing of environmental regulation pipelines and spatial adjacency between conflicting aquaculture zones.

[0010] S4. Under the constraint that the degree of regulation interference does not exceed the preset pipeline crosstalk allowable value, the marginal physiological benefit elasticity ratio is calculated based on the physiological response elasticity and marginal benefit of each growth stage to environmental parameters. The inter-stage resource competition ranking is generated according to the marginal physiological benefit elasticity ratio. Environmental regulation resources are released step by step according to the inter-stage resource competition ranking to obtain the environmental parameter regulation target value of each conflict breeding area.

[0011] S5. Based on the target values ​​of environmental parameters in each conflicting aquaculture zone, control signals are generated to drive the environmental regulation equipment in the corresponding aquaculture zone for zoned regulation.

[0012] Furthermore, S1 includes: collecting environmental parameters through sensor nodes deployed in each breeding area, including air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in the water; obtaining the preset breeding plan for each breeding area; extracting the initial release date and initial growth stage of toads in each breeding area from the preset breeding plan; calculating the number of breeding days based on the current date and the initial release date of toads; and estimating the current growth stage information of toads in each breeding area based on the initial growth stage and the number of breeding days.

[0013] Furthermore, the initial growth stage of the toads initially released in the preset breeding plan is obtained as tadpole stage, juvenile frog stage, sub-adult stage, or adult frog stage. Based on the initial growth stage and the number of days of breeding, the current growth stage information of the toads in each breeding area is deduced from the toad metamorphosis timeline table.

[0014] Furthermore, S2 includes: extracting all growth stages currently existing in the toad breeding shed based on growth stage information, and establishing a set of coexisting growth stages; obtaining the upper and lower bounds of the requirements for air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in the water for each growth stage in the set of coexisting growth stages; comparing the requirement intervals of all growth stages in the set of coexisting growth stages for each environmental parameter dimension, identifying requirement intervals that do not overlap, and determining the parameter range defined by the requirement intervals that do not overlap as the requirement incompatible intervals in the environmental parameter dimension; traversing each breeding area, and marking the breeding area where the collected value of any environmental parameter falls into the requirement incompatible interval in the environmental parameter dimension as a conflict breeding area.

[0015] Furthermore, the upper and lower bounds of air temperature requirements, air humidity requirements, water temperature requirements, light intensity requirements, and dissolved oxygen content requirements for each growth stage in the coexisting growth stage set under the conditions of breeding density are obtained.

[0016] Furthermore, S3 includes: for each conflict breeding area, determining the optimal values ​​for air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content from the upper and lower bounds of the demand at the growth stage of the conflict breeding area; calculating the absolute values ​​of the differences between the collected air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content and their corresponding optimal values ​​as deviations; obtaining the topological connection diagram of the environmental regulation pipeline in the toad breeding shed; identifying conflict breeding area pairs that share the same environmental regulation pipeline trunk; obtaining the spatial adjacency distance between conflict breeding areas; marking the regulation interference degree between conflict breeding area pairs that share the same environmental regulation pipeline trunk and whose spatial adjacency distance is lower than a preset adjacency threshold as strong interference; and marking the regulation interference degree between other conflict breeding area pairs as weak interference.

[0017] Further, S4 includes: extracting conflict aquaculture zone pairs with strong interference; classifying the conflict aquaculture zones involved in the strong interference conflict aquaculture zone pairs into a constrained conflict set; classifying the remaining conflict aquaculture zones into an unconstrained conflict set; obtaining the physiological response elasticity coefficient and marginal benefit coefficient of each growth stage to air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in water; calculating the ratio of the physiological response elasticity coefficient to the marginal benefit coefficient as the marginal physiological benefit elasticity ratio; sorting the growth stages in the coexisting growth stage set from low to high according to the marginal physiological benefit elasticity ratio to generate an inter-stage resource competition ranking; directly setting the environmental parameter control target value of the conflict aquaculture zone in each unconstrained conflict set to the optimal value of the demand range of the growth stage in which the conflict aquaculture zone is located; for the conflict aquaculture zones in each constrained conflict set, solving step by step according to the inter-stage resource competition ranking, using the upper limit of the released environmental regulation resources as a constraint, and sequentially determining the environmental parameter control target value of each conflict aquaculture zone.

[0018] Furthermore, the physiological response elasticity coefficient and marginal benefit coefficient of each growth stage to air temperature, air humidity, water temperature, light intensity and dissolved oxygen content in water were obtained. The physiological response elasticity coefficient is the rate of change in toad venom production caused by a unit change in environmental parameters, and the marginal benefit coefficient is the increase in toad venom production caused by a unit input of environmental parameter adjustment resources.

[0019] Furthermore, S5 includes: calculating the difference between the target values ​​of environmental parameter control for each conflict aquaculture zone and the real-time collected air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in the conflict aquaculture zone to obtain the environmental parameter deviation for each conflict aquaculture zone; generating control signals based on the environmental parameter deviation and a preset control cycle, the control signals including ventilation equipment start / stop commands, spray equipment start / stop commands, shading equipment adjustment commands, heating equipment power commands, and water exchange equipment flow commands; and sending the control signals to the corresponding environmental control equipment in each conflict aquaculture zone to drive the environmental control equipment to independently perform environmental control actions within the conflict aquaculture zone, thereby achieving zoned control between conflict aquaculture zones.

[0020] On the other hand, the present invention provides a big data-based toad farming environment management system, comprising the following modules:

[0021] The parameter acquisition module is used to collect environmental parameters from multiple breeding areas within the toad breeding shed and obtain information on the current growth stage of toads in each breeding area.

[0022] The aquaculture zone identification module is used to determine the set of coexisting growth stages based on growth stage information, and to determine the incompatible demand interval of the set of coexisting growth stages in each environmental parameter dimension according to the demand interval of each growth stage for environmental parameters. Aquaculture zones whose environmental parameters fall into the incompatible demand interval are marked as conflict aquaculture zones.

[0023] The interference calculation module is used to calculate the deviation between the environmental parameters of each conflicting aquaculture zone and the optimal value of the demand range of its growth stage, and to determine the regulation interference degree of each pair of conflicting aquaculture zones based on the sharing of environmental regulation pipelines and spatial adjacency between conflicting aquaculture zones.

[0024] The target value solving module is used to calculate the marginal physiological benefit elasticity ratio based on the physiological response elasticity and marginal benefit of each growth stage to environmental parameters, under the constraint that the regulation interference degree does not exceed the preset pipeline crosstalk allowable value. Based on the marginal physiological benefit elasticity ratio, the module generates the inter-stage resource competition ranking, releases environmental regulation resources step by step according to the inter-stage resource competition ranking, and obtains the environmental parameter regulation target value of each conflict aquaculture area.

[0025] The zone control module is used to generate control signals based on the target values ​​of environmental parameters in each conflicting aquaculture zone, and drive the environmental regulation equipment in the corresponding aquaculture zone to perform zone control.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. By extracting the set of coexisting growth stages and determining the incompatible intervals of demand across various environmental parameter dimensions, the identification of conflicting demands across multiple growth stages is transformed from manual experience-based judgment into a quantifiable and traceable data processing process. This avoids the drawback of compromise-based regulation across the entire field, which causes environmental parameters at each stage to deviate from their optimal range. Based on this, the degree of regulatory interference between conflicting aquaculture areas is determined by combining the shared status of environmental regulation pipelines and the spatial adjacency of aquaculture areas. This ensures that physical constraints such as pipeline crosstalk and spatial coupling are taken into account when making regulatory decisions, thereby preventing secondary fluctuations in environmental parameters caused by mutual interference of regulatory actions at the source.

[0028] 2. For the allocation of regulatory resources in constrained conflict aquaculture areas, the marginal physiological benefit elasticity ratio is calculated based on the physiological response elasticity and marginal benefit of each growth stage, and a resource competition ranking between stages is generated. Environmental regulation resources are released step by step according to the ranking, so that the limited environmental regulation capacity prioritizes the growth stages with low physiological response elasticity and high marginal resource consumption, rather than simply weighting and compromising according to the weight of the growth stages. This shifts the decision-making focus of environmental regulation from the parameter deviation itself to the changes in output benefits caused by the parameter deviation. In aquaculture scenarios where multiple stages coexist, the overall aquaculture efficiency of the entire farm can be improved without breaking the pipeline crosstalk constraints. At the same time, it provides a directly executable control signal generation path for the zonal regulation of each aquaculture area. Attached Figure Description

[0029] Figure 1 This is a flowchart of a big data-based method for controlling the environment of toad farming according to the present invention.

[0030] Figure 2 This is a schematic diagram of the structure of a big data-based toad farming environment management system according to the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0032] Example 1: Figure 1 This invention presents a method for environmental management of toad farming based on big data, which includes the following steps:

[0033] S1. Collect environmental parameters from multiple breeding areas within the toad breeding shed and obtain information on the current growth stage of toads in each breeding area;

[0034] S2. Based on growth stage information, determine the set of coexisting growth stages. According to the demand range of each growth stage for environmental parameters, determine the incompatible demand range of the set of coexisting growth stages in each environmental parameter dimension. Mark the breeding area where the environmental parameters fall into the incompatible demand range as the conflict breeding area.

[0035] S3. Calculate the deviation between the environmental parameters of each conflicting aquaculture zone and the optimal value of the demand range of its growth stage, and determine the regulation interference degree of each pair of conflicting aquaculture zones based on the sharing of environmental regulation pipelines and spatial adjacency between conflicting aquaculture zones.

[0036] S4. Under the constraint that the degree of regulation interference does not exceed the preset pipeline crosstalk allowable value, the marginal physiological benefit elasticity ratio is calculated based on the physiological response elasticity and marginal benefit of each growth stage to environmental parameters. The inter-stage resource competition ranking is generated according to the marginal physiological benefit elasticity ratio. Environmental regulation resources are released step by step according to the inter-stage resource competition ranking to obtain the environmental parameter regulation target value of each conflict breeding area.

[0037] S5. Based on the target values ​​of environmental parameters in each conflicting aquaculture zone, control signals are generated to drive the environmental regulation equipment in the corresponding aquaculture zone for zoned regulation.

[0038] In the specific implementation of S1, a set of sensor nodes is pre-deployed in each breeding area of ​​the toad breeding shed. Each set of sensor nodes consists of an air temperature sensor, an air humidity sensor, a water temperature sensor, a light intensity sensor, and a dissolved oxygen content sensor. The air temperature sensor is fixed at the crossbeam of the shade shed above the breeding area, 1 to 1.5 meters above the ground. The air humidity sensor is fixed side by side with the air temperature sensor at the same crossbeam position. The water temperature sensor is submerged at half the depth of the breeding pond water. The light intensity sensor is fixed at an unobstructed position outside the shade shed of the breeding area. The dissolved oxygen content sensor is submerged at half the depth of the breeding pond water and is at a horizontal distance of more than 1 meter from the outlet of the aeration equipment. Each group of sensor nodes transmits the collected air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content to a central controller deployed within the toad breeding shed via wired or wireless communication cables. The central controller polls each group of sensor nodes at a fixed acquisition period to obtain the current air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content values ​​for each breeding area. The central controller establishes a correspondence between these collected values ​​and the breeding area number, which is a unique numerical identifier pre-assigned to each breeding area. The fixed acquisition period is determined based on the maximum rate of change of environmental parameters within the toad breeding shed under normal operating conditions; for example, the fixed acquisition period may be set to 5 minutes or 10 minutes.

[0039] Obtain the pre-set breeding plans for each breeding area. These plans are breeding management records compiled by the toad farm for each batch of toads released. The records include the breeding area number, the date of initial toad release, and the initial growth stage of the released toads. The date of initial toad release is recorded in year-month-day format. The initial growth stage of the released toads is one of the following: tadpole stage, juvenile frog stage, sub-adult stage, or adult frog stage. The tadpole stage refers to the toad population development period from hatching to metamorphosis and coming ashore. The juvenile frog stage refers to the toad population development period from coming ashore to reaching the pre-set weight for separation into different ponds. The sub-adult stage refers to the toad population development period from separation into different ponds to reaching the pre-set weight for toad venom harvesting. The adult frog stage refers to the toad population development period when the toad population has reached the pre-set weight for toad venom harvesting and is ready for venom collection. Extract the breeding zone number, the initial release date of toads, and the initial growth stage of the toads for each breeding zone from the preset breeding plan. Read the current date from the real-time clock module of the central controller. The current date is also in year-month-day format. Calculate the number of days between the current date and the initial release date of the toads. This date interval is the number of days the breeding zone has been in operation. The date interval is calculated by converting the current date's year-month-day format to a day ordinal number, converting the initial release date's year-month-day format to a day ordinal number, and then subtracting the initial release date's day ordinal number from the current date's day ordinal number to obtain the absolute value of the difference.

[0040] A pre-established metamorphosis timeline table for toads was obtained. This table is a reference table for developmental duration compiled based on statistical values ​​of the actual number of days it takes for toad populations to develop from each initial growth stage to the next adjacent growth stage, recorded in multiple complete breeding cycles at toad farms. The table uses the initial growth stage as an index and records the lower and upper limits of the number of days required to develop from the initial growth stage to the next adjacent growth stage under different water temperature ranges. For example, the entry in the table corresponding to the tadpole stage as the initial growth stage records that the number of days required to develop from the tadpole stage to the froglet stage is 45 to 55 days when the water temperature range is 20℃ to 24℃, and 35 to 45 days when the water temperature range is 24℃ to 28℃. The entry corresponding to the initial growth stage of tadpoles states that the development time from tadpoles to subadults is 60 to 70 days when the water temperature is between 22°C and 26°C. The entry corresponding to the initial growth stage of subadults states that the development time from subadults to adult frogs is 80 to 90 days when the water temperature is between 24°C and 28°C. The logic for calculating the current growth stage information of toads in each breeding area is as follows: Search the toad metamorphosis timeline table for entries matching the initial growth stage of the breeding area; obtain the current water temperature value of the breeding area and determine the water temperature range it falls into; read the lower and upper limits of the number of development days required to progress from the initial growth stage to the next adjacent growth stage corresponding to the water temperature range; compare the number of days already bred with the lower and upper limits of the development days; if the number of days already bred is less than the lower limit of the development days, the current growth stage information of the toads in the breeding area is determined to be the initial growth stage; if the number of days already bred is greater than or equal to the upper limit of the development days, then recursively calculate the next adjacent growth stage along the growth stage recursion path recorded in the toad metamorphosis timeline table, and then repeat the above search and comparison process using this next adjacent growth stage as the new initial growth stage, until the number of days already bred falls within the range formed by the lower and upper limits of the development days corresponding to a certain growth stage, and then this growth stage is determined as the current growth stage information of the toads in the breeding area. For example, the initial growth stage of a certain breeding area is the tadpole stage. The current water temperature is 25℃, falling within the water temperature range of 24℃ to 28℃. The breeding days are 80 days. From the toad metamorphosis timeline table, the development days from tadpole stage to froglet stage are 35 to 45 days, from froglet stage to sub-adult stage are 60 to 70 days, and from sub-adult stage to adult frog stage are 80 to 90 days. 80 days is greater than 45 days and greater than 70 days. 80 days is less than the lower limit of 80 days for the development days from sub-adult stage to adult frog stage. Therefore, the current growth stage of the toads in this breeding area is calculated to be the sub-adult stage.

[0041] In the specific implementation of S2, based on the current growth stage information of toads in each breeding area obtained in step S1, all growth stages currently existing in the toad breeding shed are extracted to establish a coexisting growth stage set. The extraction method involves traversing the growth stage information of all breeding areas and adding each unique growth stage to the coexisting growth stage set. When any two or more of the following growth stages—tadpole stage, juvenile stage, subadult stage, and adult stage—simultaneously exist in different breeding areas within the toad breeding shed, the coexisting growth stage set will contain the corresponding multiple growth stages. For example, after traversal, the coexisting growth stage set contains three growth stages: tadpole stage, juvenile stage, and adult stage, indicating that the toad breeding shed currently simultaneously contains breeding areas in the tadpole stage, breeding areas in the juvenile stage, and breeding areas in the adult stage.

[0042] The upper and lower bounds of air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content requirements for each growth stage within the coexisting growth stage set were obtained under the given stocking density conditions. The requirement ranges for each growth stage across these environmental parameters were pre-determined based on historical data corresponding to environmental parameter records accumulated over multiple complete breeding cycles and toad population growth indicators from the toad farm. The determination method involves retrieving the corresponding breeding logs from the historical breeding database for each individual growth stage. These logs record daily air temperature, air humidity, water temperature, light intensity, dissolved oxygen content, and the daily growth status evaluation of the toad population. The growth status evaluation includes scores for feeding activity, skin luster, and the incidence of abnormal behavior. The minimum air temperature value corresponding to records with growth status evaluation results within the normal range is taken as the lower bound of the air temperature requirement, and the maximum value is taken as the upper bound. The minimum value of the collected air humidity is taken as the lower bound of the air humidity requirement, and the maximum value is taken as the upper bound of the air humidity requirement. The minimum value of the collected water temperature corresponding to the record whose growth status evaluation result is within the normal scoring range is taken as the lower bound of the water temperature requirement, and the maximum value is taken as the upper bound of the water temperature requirement. The minimum value of the collected light intensity corresponding to the record whose growth status evaluation result is within the normal scoring range is taken as the lower bound of the light intensity requirement, and the maximum value is taken as the upper bound of the light intensity requirement. The minimum value of the collected dissolved oxygen content corresponding to the record whose growth status evaluation result is within the normal scoring range is taken as the lower bound of the dissolved oxygen content requirement, and the maximum value is taken as the upper bound of the dissolved oxygen content requirement. The stocking density condition refers to the shift in the environmental parameter requirements of toad populations under different stocking densities. The requirement range is obtained by adding a stocking density filter when retrieving historical stocking databases. Stocking density conditions are distinguished by the number of toads per unit area; for example, a stocking density below 20 toads / m² is considered low-density, between 20 and 40 toads / m² is medium-density, and above 40 toads / m² is high-density. For low-density, medium-density, and high-density conditions, corresponding upper and lower bounds for air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content are extracted using the same method. When obtaining the requirement range, it is determined which stocking density condition the current stocking density of each area falls under, i.e., the corresponding upper and lower bounds for that stocking density condition are selected.

[0043] For each environmental parameter dimension, the demand intervals of all growth stages in the coexisting growth stage set are compared to identify non-overlapping demand intervals. The parameter range defined by these non-overlapping demand intervals is determined as an incompatible demand interval on the environmental parameter dimension. The comparison method involves selecting the air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content dimensions respectively, and performing interval intersection determination one by one. Taking the air temperature dimension as an example, the upper and lower bounds of the air temperature demand under the stocking density conditions for each growth stage in the coexisting growth stage set are extracted to obtain multiple air temperature demand intervals. These multiple air temperature demand intervals are plotted on the same temperature axis. The coverage of each air temperature demand interval is checked segment by segment along the temperature axis from low to high temperature. When a temperature segment on the temperature axis is covered by the air temperature demand intervals of some growth stages but has no overlap with the air temperature demand intervals of other growth stages, this temperature segment is identified as a non-overlapping demand interval. The temperature range defined by the lower and upper bounds of this temperature segment is an incompatible demand interval on the air temperature dimension. The same interval intersection determination method is used for the dimensions of air humidity, water temperature, light intensity, and dissolved oxygen content. For example, the set of coexisting growth stages includes the tadpole stage and the adult frog stage. The water temperature requirement range for the tadpole stage under low-density breeding conditions is 22℃ to 28℃, and the water temperature requirement range for the adult frog stage under low-density breeding conditions is 18℃ to 24℃. The two water temperature requirement ranges intersect between 22℃ and 24℃. However, the 18℃ to 22℃ range is only covered by the adult frog stage and not by the tadpole stage, and the 24℃ to 28℃ range is only covered by the tadpole stage and not by the adult frog stage. Therefore, both 18℃ to 22℃ and 24℃ to 28℃ are determined to be incompatible intervals in terms of water temperature requirements.

[0044] Each aquaculture zone is traversed, and zones where any environmental parameter's collected value falls within the incompatible range of requirements in the environmental parameter dimension are marked as conflict aquaculture zones. The traversal method involves checking each aquaculture zone individually to see if its collected air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content fall within the incompatible range of requirements in the air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content dimensions. When a particular environmental parameter's collected value in an aquaculture zone falls within the incompatible range of requirements in that dimension, it means that although the current environmental parameter value is within the required range for its own growth stage, it has fallen into a parameter range unacceptable to other growth stages in the coexisting growth stage set. Continuing to maintain this environmental parameter value will damage the physiological state of other growth stages in the coexisting growth stage set; therefore, this aquaculture zone is marked as a conflict aquaculture zone. The marking information for conflict-affected aquaculture zones includes the zone number and the name of the environmental parameter dimension that triggered the marking. This marking information is used to identify aquaculture zones that require priority ranking and zonal control in subsequent steps. The marking information for conflict-affected aquaculture zones, along with the zone number, the current environmental parameter values, and the growth stage information, are stored in the storage unit of the central controller.

[0045] In the specific implementation of S3, for each conflict aquaculture zone, the optimal values ​​for air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content are determined from the upper and lower bounds of the demand under the stocking density conditions at the growth stage of the conflict aquaculture zone. The upper and lower bounds of the demand have already been obtained and stored in the storage unit of the central controller in step S2. The optimal air temperature value is determined by retrieving the corresponding growth stage information and stocking density conditions for each conflict aquaculture zone, reading the upper and lower bounds of the air temperature demand under the stocking density conditions at the growth stage from the storage unit, and taking the midpoint between the upper and lower bounds as the optimal air temperature value. The midpoint is calculated as the sum of the upper and lower bounds of the air temperature demand, divided by 2. The optimal air humidity value is determined by taking the midpoint between the upper and lower bounds of the air humidity demand, calculated as the sum of the upper and lower bounds of the air humidity demand, divided by 2. The optimal water temperature is determined by taking the midpoint between the upper and lower bounds of the required water temperature. This midpoint is calculated by adding the upper and lower bounds of the required water temperature and then dividing by 2. Similarly, the optimal light intensity is determined by taking the midpoint between the upper and lower bounds of the required light intensity and then dividing by 2. Likewise, the optimal dissolved oxygen content is determined by taking the midpoint between the upper and lower bounds of the required dissolved oxygen content and then dividing by 2. In another method, the optimal values ​​for air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content can be determined based on the environmental parameter values ​​corresponding to the records with the highest growth status evaluation scores for toad populations at different growth stages and stocking densities in the historical aquaculture database. Specifically, this involves selecting records from the historical aquaculture database that rank among the top percentages in the comprehensive score of feeding activity, skin luster, and abnormal behavior incidence rates under different growth stages and stocking densities. The average of the corresponding air temperature values ​​is taken as the optimal air temperature value; the average of the corresponding air humidity values ​​is taken as the optimal air humidity value; the average of the corresponding water temperature values ​​is taken as the optimal water temperature value; the average of the corresponding light intensity values ​​is taken as the optimal light intensity value; and the average of the corresponding dissolved oxygen content values ​​is taken as the optimal dissolved oxygen content value. The top percentages in the comprehensive score are pre-set proportions, for example, the top 10% in the comprehensive score.

[0046] The absolute value of the difference between the collected air temperature and the optimal air temperature value in the conflict aquaculture zone is calculated as the air temperature deviation; the absolute value of the difference between the collected air humidity and the optimal air humidity value in the conflict aquaculture zone is calculated as the air humidity deviation; the absolute value of the difference between the collected water temperature and the optimal water temperature value in the conflict aquaculture zone is calculated as the water temperature deviation; the absolute value of the difference between the collected light intensity and the optimal light intensity value in the conflict aquaculture zone is calculated as the light intensity deviation; and the absolute value of the difference between the collected dissolved oxygen content in the conflict aquaculture zone and the optimal dissolved oxygen content in the water is calculated as the dissolved oxygen content deviation. The air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content collected in the conflict aquaculture zone are the environmental parameter collection values ​​at the current moment, collected by sensor nodes and stored in the storage unit of the central controller in step S1. The deviation reflects the degree of deviation between the current environmental parameter collection values ​​and their optimal values ​​in the conflict aquaculture zone. The larger the deviation, the further the environmental parameter collection values ​​in the conflict aquaculture zone are from the optimal values, and the more environmental regulation resources are needed to bring them back to the optimal values.

[0047] A topological connection diagram of the environmental regulation pipelines within the toad breeding shed is obtained. This diagram is a digital copy of the pipeline layout drawings created during the design and construction phases or subsequent renovations of the toad breeding shed. The diagram indicates the direction of each main environmental regulation pipeline, the direction of each branch pipeline, the connection points of each breeding area on the branch pipelines, and the area covered by each main pipeline. Each main environmental regulation pipeline corresponds to a specific environmental regulation medium, including hot water, cold water, steam, spray water, and air. Conflicting breeding area pairs sharing the same main environmental regulation pipeline are identified by traversing each main environmental regulation pipeline recorded in the topological connection diagram, extracting the set of conflicting breeding areas connected to each main pipeline, and pairing the conflicting breeding areas in each set to obtain the pairs of conflicting breeding areas sharing the same main environmental regulation pipeline.

[0048] The spatial adjacency distance between conflicting breeding areas is obtained based on a plan view of the toad breeding shed. The plan view marks the coordinates of the center points of each breeding area, and the spatial adjacency distance between conflicting breeding areas is the straight-line distance between the coordinates of the center points of two conflicting breeding areas. The preset adjacency distance threshold is a distance value pre-set based on the distribution density of the branch pipes of the environmental regulation pipeline within the toad breeding shed and the blocking effect of airflow barriers between breeding areas. The preset adjacency distance threshold is set based on the fact that when the spatial adjacency distance between two breeding areas is less than the preset threshold, the impact of environmental regulation actions performed in one breeding area on the environmental parameters of the other breeding area exceeds the upper limit of the tolerable crosstalk level. The preset adjacency distance threshold is determined by selecting multiple pairs of breeding areas at different distances within the toad breeding shed for unilateral control experiments. A step-type environmental regulation action is applied in one breeding area, and the change in the corresponding environmental parameters in the other breeding area is measured. The spatial distance at which the proportion of the change in the step amplitude first falls below the preset crosstalk ratio threshold is set as the preset adjacency distance threshold. The preset crosstalk ratio threshold is, for example, 10%.

[0049] The regulation interference between conflicting aquaculture zones sharing the same environmental regulation pipeline trunk line and having a spatial adjacency distance below a preset adjacency distance threshold is marked as strong interference. Strong interference indicates that the two conflicting aquaculture zones in a pair share the same regulation resource at the environmental regulation pipeline trunk line level and exhibit significant crosstalk at the spatial level, making it impossible to independently regulate one conflicting aquaculture zone without affecting the other beyond the permissible crosstalk level. The regulation interference between conflicting aquaculture zones sharing the same environmental regulation pipeline trunk line but having a spatial adjacency distance greater than or equal to a preset adjacency distance threshold is marked as weak interference. The regulation interference between conflicting aquaculture zones not sharing any environmental regulation pipeline trunk line is also marked as weak interference. Weak interference indicates that there is no pipeline-level sharing constraint between the two conflicting aquaculture zones in a pair, or although they share the same environmental regulation pipeline trunk line, the spatial adjacency distance is large enough that the degree of crosstalk is within the permissible range. When regulating the environment of the conflicting aquaculture zones in the pair, the degree of mutual interference is low, and relatively independent regulation can be carried out according to their respective needs.

[0050] In the specific implementation of S4, the conflicting aquaculture zone pairs with strong interference levels identified in step S3 are extracted. All conflicting aquaculture zones involved in these pairs are categorized into a constrained conflict set. These conflicting aquaculture zones in the constrained conflict set are subject to dual constraints: shared environmental control pipeline trunk lines and spatial adjacency distances below a preset threshold. This means that environmental control of any conflicting aquaculture zone within the constrained conflict set will inevitably have an impact exceeding the allowable crosstalk level on other conflicting aquaculture zones within the set. Therefore, conflicting aquaculture zones in the constrained conflict set cannot independently set their own environmental parameter control target values; they must be coordinated to allocate limited environmental control resources while satisfying crosstalk constraints. The remaining conflicting aquaculture zones not included in the constrained conflict set are categorized into an unconstrained conflict set. These remaining conflicting aquaculture zones include those involved in the weak interference pairs but not appearing in any strong interference pairs. In an unconstrained conflict set, conflicting aquaculture zones either do not share any environmental regulation pipeline trunks, or although they share the same environmental regulation pipeline trunks, their spatial adjacency distance is greater than or equal to a preset adjacency distance threshold. The degree of crosstalk between them is within the allowable range, and each can independently set environmental parameter control target values ​​without affecting other conflicting aquaculture zones beyond the allowable level of crosstalk.

[0051] The physiological response elasticity coefficients and marginal benefit coefficients for each growth stage in response to air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in the water were obtained. The physiological response elasticity coefficient represents the rate of change in toad venom production caused by a unit change in environmental parameters, while the marginal benefit coefficient represents the increase in toad venom production caused by a unit input of resources to regulate environmental parameters. The physiological response elasticity coefficients and marginal benefit coefficients for each growth stage at different environmental parameter dimensions were obtained based on experimental data accumulated by the toad farm over multiple complete breeding cycles. The experimental data collection method involved conducting a single-factor gradient regulation experiment on a specific environmental parameter dimension for a single growth stage, keeping other environmental parameters constant. The actual value of the environmental parameter at each gradient and the toad venom production value at the end of the corresponding breeding cycle were recorded. The difference between the toad venom production values ​​of adjacent gradients and the difference between the actual values ​​of the environmental parameters were calculated. The physiological response elasticity coefficient was obtained by dividing the difference in toad venom production values ​​by the difference in the actual values ​​of the environmental parameters. For example, in a single-factor gradient regulation experiment of water temperature during the adult frog stage, water temperature gradients of 18℃, 20℃, 22℃, 24℃, and 26℃ were set. Under the premise that the optimal values ​​of air temperature, air humidity, light intensity, and dissolved oxygen content in the water remained constant at the optimal values ​​for the adult frog stocking density, frogs were raised at each water temperature gradient until the venom collection period, and the corresponding venom yield per unit area was recorded. When the water temperature changed from 20℃ to 22℃, the venom yield per unit area changed from, for example, 50 g / m² to, for example, 55 g / m². The physiological response elasticity coefficient was calculated by subtracting, for example, 50 g / m² from 55 g / m² and dividing by the difference between 22℃ and 20℃, resulting in, for example, 2.5 g / m²·℃. The above single-factor gradient regulation experiment was performed for different growth stages and different environmental parameter dimensions to obtain the physiological response elasticity coefficients of each growth stage to air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in the water. The marginal benefit coefficient is obtained by progressively increasing the input of a specific environmental regulation resource for a single growth stage, while maintaining environmental parameters at the optimal value within the demand range under the breeding density conditions of that stage. The unit of measurement for the environmental regulation resource input is determined according to different environmental regulation media: the input of hot water is measured in liters per minute (L / min), the input of cold water is measured in L / min, the input of spray water is measured in L / min, and the input of air is measured in cubic meters per minute (m³ / min). The corresponding toad venom yield value under each level of environmental regulation resource input is recorded, and the ratio of the increase in toad venom yield value between adjacent input levels to the increase in environmental regulation resource input is calculated as the marginal benefit coefficient.For example, the marginal benefit coefficient of water temperature during the adult frog stage is obtained by gradually increasing the hot water volume flow rate at each stage, for example, by 2 liters / minute, while maintaining a steady state. The yield of toad venom per unit area is recorded at each stage of hot water volume flow rate. When the hot water volume flow rate increases from, for example, 4 liters / minute to, for example, 6 liters / minute, the yield of toad venom per unit area increases from, for example, 55 grams / square meter to, for example, 58 grams / square meter. The marginal benefit coefficient is, for example, 58 grams / square meter minus, for example, 55 grams / square meter, divided by, for example, 6 liters / minute minus, for example, 4 liters / minute, resulting in, for example, 1.5 grams per minute / square meter / liter.

[0052] The ratio of the physiological response elasticity coefficient to the marginal benefit coefficient for each environmental parameter at each growth stage is calculated as the marginal physiological benefit elasticity ratio. The calculation method involves dividing the physiological response elasticity coefficient by the marginal benefit coefficient for the same growth stage and the same environmental parameter dimension. The resulting ratio is a composite unit representing the input of environmental regulation resources and the toad venom production. The marginal physiological benefit elasticity ratio reflects the efficiency of the change in toad venom production resulting from the physiological response mechanism, which can be obtained by investing a unit of environmental regulation resources in the environmental parameter dimension at a given growth stage. A lower marginal physiological benefit elasticity ratio indicates that the growth stage is less sensitive to increases in toad venom production under the same input of environmental regulation resources, requiring priority to ensure the supply of environmental regulation resources to maintain its basic physiological state. Conversely, a higher marginal physiological benefit elasticity ratio indicates that the growth stage is more sensitive to increases in toad venom production under the same input of environmental regulation resources, allowing for a relatively later allocation of limited environmental regulation resources.

[0053] The growth stages in the coexisting growth stage set are sorted from lowest to highest based on their marginal physiological benefit elasticity ratio, generating an inter-stage resource competition ranking. The growth stage with the lowest marginal physiological benefit elasticity ratio is ranked first, and the growth stage with the highest marginal physiological benefit elasticity ratio is ranked last. Growth stages ranked higher in the inter-stage resource competition ranking enjoy higher priority in the competition for environmental regulation resources. For example, if the coexisting growth stage set includes tadpole, juvenile, and adult frog stages, and the marginal physiological benefit elasticity ratio of the tadpole stage to water temperature is, for example, 0.3 L·min / m²·g, the juvenile stage's marginal physiological benefit elasticity ratio to water temperature is, for example, 0.5 L·min / m²·g, and the adult frog stage's marginal physiological benefit elasticity ratio to water temperature is, for example, 0.8 L·min / m²·g, then the inter-stage resource competition ranking for water temperature, after sorting by marginal physiological benefit elasticity ratio from lowest to highest, would be: tadpole stage first, juvenile stage second, and adult frog stage third.

[0054] In the unconstrained conflict set, the target values ​​for environmental parameter regulation of conflict aquaculture zones are directly set to the optimal values ​​within the demand range under the stocking density conditions at the growth stage of the conflict aquaculture zone. The optimal values ​​within the demand range are the optimal values ​​for air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content determined in step S3. Because the conflict aquaculture zones in the unconstrained conflict set do not have constraints with a strong interference level, they can independently perform optimal environmental regulation without affecting other aquaculture zones beyond the allowable crosstalk level. Therefore, the target values ​​for environmental parameter regulation of conflict aquaculture zones in the unconstrained conflict set are directly set to the optimal values ​​within the demand range to achieve the best growth state for the conflict aquaculture zones. For conflict aquaculture zones in the constrained conflict set, the target values ​​for environmental parameter regulation of each conflict aquaculture zone are solved step-by-step according to the resource competition ranking between stages. The step-by-step solution process begins with the growth stage, ranked first in the inter-stage resource competition ranking. It retrieves all conflicting breeding areas within the first-ranked growth stage from the constrained conflict set. The initial environmental parameter control target values ​​for each retrieved conflicting breeding area are set as the optimal values ​​within their respective demand intervals. The total amount of environmental regulation resources required to adjust the retrieved conflicting breeding areas from their current environmental parameter collection values ​​to their respective optimal demand interval values ​​is calculated. This total amount of environmental regulation resources is compared with a preset upper limit for environmental regulation resource supply. This upper limit is based on the total rated power of the environmental regulation equipment in the toad breeding shed and the maximum transport capacity of the pipelines, setting the upper limit for the flow rate of each environmental regulation medium. When the required total amount of environmental regulation resources does not exceed the upper limit, the environmental parameter control target values ​​for the retrieved conflicting breeding areas are determined as the optimal values ​​within their respective demand intervals. The occupied environmental regulation resources are deducted from the upper limit, releasing the remaining available environmental regulation resources for the next-ranked growth stage in the inter-stage resource competition ranking. The remaining upper limit of environmental regulation resources after the initial allocation is then passed on as the released upper limit to the next-ranked growth stage in the inter-stage resource competition ranking. When the total amount of environmental regulation resources required for a certain growth stage in the inter-stage resource competition ranking exceeds the current upper limit of the remaining environmental regulation resources, the deviations of each conflicting aquaculture area within the certain growth stage calculated by step S3 are sorted from largest to smallest. The remaining available environmental regulation resources are then used to satisfy each conflicting aquaculture area in descending order of deviation to approach the optimal value of the demand interval from the current environmental parameter collection value, until the upper limit of the environmental regulation resources is completely exhausted. The target value of environmental parameter regulation for conflicting aquaculture areas that have not obtained sufficient environmental regulation resources is determined as the closest parameter value that can be approached under the current constraints of the remaining environmental regulation resources.The calculation process is performed sequentially downwards from the first growth stage, based on the resource competition among stages, until the environmental parameter control target values ​​of all conflicting aquaculture areas in the constrained conflict set are determined, or the upper limit of environmental regulation resource supply has been fully allocated, at which point the calculation terminates.

[0055] In the specific implementation of S5, the environmental parameter control target values ​​for each conflict aquaculture zone obtained in step S4 are retrieved from the storage unit of the central controller. These environmental parameter control target values ​​include air temperature control target values, air humidity control target values, water temperature control target values, light intensity control target values, and dissolved oxygen content control target values. From the environmental parameter acquisition values ​​collected by sensor nodes in step S1 and stored in the central controller's storage unit at the current moment, the real-time collected air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content values ​​for each conflict aquaculture zone are read. For each conflict-affected aquaculture zone, a difference calculation is performed. The difference calculation is as follows: air temperature deviation is obtained by subtracting the collected air temperature value from the target air temperature control value; air humidity deviation is obtained by subtracting the collected air humidity value from the target air humidity control value; water temperature deviation is obtained by subtracting the collected water temperature value from the target water temperature control value; light intensity deviation is obtained by subtracting the collected light intensity value from the target light intensity control value; and dissolved oxygen deviation is obtained by subtracting the collected dissolved oxygen value from the target water oxygen content control value. The deviations of air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content are collectively referred to as environmental parameter deviations. Environmental parameter deviations have positive and negative directions. A positive deviation indicates that the current collected environmental parameter value is lower than the target value, requiring an increase in the output of the corresponding environmental parameter; a negative deviation indicates that the current collected environmental parameter value is higher than the target value, requiring a decrease in the output of the corresponding environmental parameter. The deviations in air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in each conflict aquaculture zone are stored in the storage unit of the central controller.

[0056] Control signals are generated based on environmental parameter deviations and a preset control cycle. These signals include start / stop commands for ventilation equipment, misting equipment, shading equipment, heating equipment, and water exchange equipment. The preset control cycle is the interval for updating control commands, set according to the response time constant of environmental parameters within the toad breeding shed under normal disturbances. The preset control cycle is set by selecting a typical breeding area within the toad breeding shed, applying a step-type environmental adjustment action, and continuously collecting the response curves of environmental parameters. The time required for the environmental parameters to reach 63% of the step amplitude is taken as the response time constant. Half to one-third of this response time constant is used as the preset control cycle interval. For example, if the response time constant is 6 minutes, the preset control cycle interval is set to 2 or 3 minutes. The central controller executes a control signal generation process once at the beginning of each control cycle. The method for generating ventilation equipment start / stop commands is as follows: for each conflict breeding area, the absolute value of the air temperature deviation is compared with a pre-set dead zone threshold for air temperature deviation. The dead zone threshold is an allowable error range to prevent frequent start / stop of the ventilation equipment. The dead zone threshold is set based on a trade-off between the equipment depreciation and energy costs incurred by the ventilation equipment during a single start / stop and the economic losses caused by small air temperature deviations to toad venom production. For example, the dead zone threshold is set to 0.5℃. When the absolute value of the air temperature deviation is less than or equal to the dead zone threshold, the ventilation equipment start / stop command is set to maintain the current state. When the absolute value of the air temperature deviation is greater than the dead zone threshold and the air temperature deviation is positive, the ventilation equipment start / stop command is set to shut down the ventilation equipment to reduce heat loss. When the absolute value of the air temperature deviation is greater than the dead zone threshold and the air temperature deviation is negative, the ventilation equipment start / stop command is set to turn on the ventilation equipment to accelerate heat dissipation and cooling. The method for generating start / stop commands for the spraying equipment involves comparing the air humidity deviation with a pre-set dead zone threshold for each conflict breeding area. The dead zone threshold is set based on a trade-off between the water consumption and equipment wear and tear from each start / stop of the spraying equipment and the economic loss caused by minor air humidity deviations to toad venom production. For example, the dead zone threshold might be set to 3% relative humidity. When the absolute value of the air humidity deviation is less than or equal to the dead zone threshold, the start / stop command for the spraying equipment is set to maintain the current state. When the absolute value of the air humidity deviation is greater than the dead zone threshold and the deviation is positive, the start / stop command is set to turn on the spraying equipment to increase air humidity. When the absolute value of the air humidity deviation is greater than the dead zone threshold and the deviation is negative, the start / stop command is set to turn off the spraying equipment to reduce air humidity.The method for generating shading device adjustment commands is as follows: for each conflicting aquaculture zone, the opening adjustment amount of the shading device is determined based on the positive or negative direction and absolute value of the light intensity deviation. The shading device is an adjustable-ratio motorized shading curtain. The shading device adjustment command includes the shading curtain opening adjustment direction and the shading curtain opening adjustment step size. When the light intensity deviation is positive, the shading curtain opening adjustment direction is to decrease the shading rate to increase the incident light, and the shading curtain opening adjustment step size is proportional to the absolute value of the light intensity deviation. When the light intensity deviation is negative, the shading curtain opening adjustment direction is to increase the shading rate to decrease the incident light, and the shading curtain opening adjustment step size is proportional to the absolute value of the light intensity deviation. The method for generating heating equipment power commands is as follows: for each conflicting aquaculture zone, the water heating equipment power command and the air heating equipment power command are determined based on the water temperature deviation and the air temperature deviation, respectively. The power command for the water heating equipment is generated by multiplying the water temperature deviation by a preset proportional coefficient for water temperature control, plus the product of the cumulative value of the water temperature deviation over a preset control period and a preset integral coefficient for water temperature control. This product forms the base value for the power command. The preset proportional and integral coefficients for water temperature control are obtained through pre-calibration via a system identification test comparing the power of the water heating equipment with the water temperature response. When the base value of the power command is positive, the power command is set to the base value and limited to the rated power limit of the water heating equipment. When the base value is negative, the power command is set to zero. The method for generating flow commands for water exchange equipment involves comparing the deviation in dissolved oxygen content (DOO) in each conflict aquaculture zone with a pre-set dead zone threshold for DOO deviation. The dead zone threshold is set based on a trade-off between the water and energy consumption of a single start-up and shutdown of the water exchange equipment and the economic loss caused by a small DOO deviation in toad venom production. For example, the dead zone threshold might be set to 0.5 mg / L. When the absolute value of the DOO deviation is less than or equal to the dead zone threshold, the flow command for the water exchange equipment is set to zero. When the absolute value of the dissolved oxygen content deviation exceeds the dead zone threshold and the deviation is positive, the flow command of the water exchange equipment is set to the preset fresh water injection flow rate. This preset flow rate is pre-set based on the aquaculture pond volume and recommended water exchange rate. For example, if the pond volume is 10 cubic meters and the recommended water exchange rate is one-tenth of the pond volume per hour, the preset fresh water injection flow rate is set to 1 cubic meter per hour. When the absolute value of the dissolved oxygen content deviation exceeds the dead zone threshold and the deviation is negative, the flow command of the water exchange equipment is set to zero, and the aeration equipment is triggered to increase the dissolved oxygen content in the water using a single aeration method without water exchange.

[0057] Control signals are sent to the corresponding environmental control equipment in each conflict aquaculture zone, driving the equipment to independently perform environmental control actions within the zone, thus achieving zoned control between the conflict aquaculture zones. The control signals are sent via wired communication cables from the central controller to the motor controllers of the ventilation equipment in each conflict aquaculture zone, to the solenoid valves of the spray equipment, to the stepper motor drivers of the shading equipment, to the thyristor power regulators of the heating equipment, and to the variable frequency pump controllers of the water exchange equipment. The centralized controller sends control signals to all conflict breeding zones in parallel within the same control cycle. Upon receiving the corresponding control signal, the environmental control equipment in each conflict breeding zone independently executes environmental control actions. These actions include starting or stopping the ventilation equipment motors, opening or closing the solenoid valves of the spraying equipment, rotating the stepper motors of the shading equipment forward or backward by the number of steps corresponding to the command, adjusting the heating power of the heating equipment to the power value corresponding to the command, and adjusting the variable frequency water pumps of the water exchange equipment to the speed corresponding to the command to output the new water injection flow rate value corresponding to the command. Since the environmental parameter control target values ​​for each conflict breeding zone have already considered the regulation interference constraints between conflict breeding zones in step S4, the crosstalk disturbances between the environmental control equipment in each conflict breeding zone are controlled within the allowable range when they execute their respective environmental control actions in parallel within the same control cycle. Each conflict breeding zone independently completes environmental control according to its own environmental parameter control target values, thereby achieving zoned control between conflict breeding zones within the toad breeding shed where multiple growth stages coexist.

[0058] Example 2: Figure 2 A schematic diagram of a big data-based toad farming environment management system is provided. This system includes the following modules:

[0059] The parameter acquisition module is used to collect environmental parameters from multiple breeding areas within the toad breeding shed and obtain information on the current growth stage of toads in each breeding area.

[0060] The aquaculture zone identification module is used to determine the set of coexisting growth stages based on growth stage information, and to determine the incompatible demand interval of the set of coexisting growth stages in each environmental parameter dimension according to the demand interval of each growth stage for environmental parameters. Aquaculture zones whose environmental parameters fall into the incompatible demand interval are marked as conflict aquaculture zones.

[0061] The interference calculation module is used to calculate the deviation between the environmental parameters of each conflicting aquaculture zone and the optimal value of the demand range of its growth stage, and to determine the regulation interference degree of each pair of conflicting aquaculture zones based on the sharing of environmental regulation pipelines and spatial adjacency between conflicting aquaculture zones.

[0062] The target value solving module is used to calculate the marginal physiological benefit elasticity ratio based on the physiological response elasticity and marginal benefit of each growth stage to environmental parameters, under the constraint that the regulation interference degree does not exceed the preset pipeline crosstalk allowable value. Based on the marginal physiological benefit elasticity ratio, the module generates the inter-stage resource competition ranking, releases environmental regulation resources step by step according to the inter-stage resource competition ranking, and obtains the environmental parameter regulation target value of each conflict aquaculture area.

[0063] The zone control module is used to generate control signals based on the target values ​​of environmental parameters in each conflicting aquaculture zone, and drive the environmental regulation equipment in the corresponding aquaculture zone to perform zone control.

[0064] The calculations involved in the embodiments are all dimensionless numerical calculations, and the preset parameters and thresholds in the calculations are set by those skilled in the art according to the actual situation.

[0065] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0066] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and inventive constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0067] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0068] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0069] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0070] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for environmental management and control of toad farming based on big data, characterized in that, Includes the following steps: S1. Collect environmental parameters from multiple breeding areas within the toad breeding shed and obtain information on the current growth stage of toads in each breeding area; S2. Based on growth stage information, determine the set of coexisting growth stages. According to the demand range of each growth stage for environmental parameters, determine the incompatible demand range of the set of coexisting growth stages in each environmental parameter dimension. Mark the breeding area where the environmental parameters fall into the incompatible demand range as the conflict breeding area. S3. Calculate the deviation between the environmental parameters of each conflicting aquaculture zone and the optimal value of the demand range of its growth stage, and determine the regulation interference degree of each pair of conflicting aquaculture zones based on the sharing of environmental regulation pipelines and spatial adjacency between conflicting aquaculture zones. S4. Under the constraint that the degree of regulation interference does not exceed the preset pipeline crosstalk allowable value, the marginal physiological benefit elasticity ratio is calculated based on the physiological response elasticity and marginal benefit of each growth stage to environmental parameters. The inter-stage resource competition ranking is generated according to the marginal physiological benefit elasticity ratio. Environmental regulation resources are released step by step according to the inter-stage resource competition ranking to obtain the environmental parameter regulation target value of each conflict breeding area. S5. Based on the target values ​​of environmental parameters in each conflicting aquaculture zone, control signals are generated to drive the environmental regulation equipment in the corresponding aquaculture zone for zoned regulation.

2. The method for managing the toad farming environment based on big data according to claim 1, characterized in that, S1 includes: Environmental parameters, including air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content, are collected by sensor nodes deployed in each breeding area. The preset breeding plan for each breeding area is obtained, and the date of initial release of toads and the initial growth stage are extracted from the preset breeding plan. The number of days of breeding is calculated by combining the current date with the date of initial release of toads. Based on the initial growth stage and the number of days of breeding, the current growth stage information of toads in each breeding area is estimated.

3. The method for managing the toad farming environment based on big data according to claim 2, characterized in that, The initial growth stage of the toads initially released in the preset breeding plan is obtained, which is either tadpole stage, juvenile frog stage, subadult stage, or adult frog stage. Based on the initial growth stage and the number of days of breeding, the current growth stage information of the toads in each breeding area is calculated from the toad metamorphosis timeline table.

4. The method for managing the toad farming environment based on big data according to claim 1, characterized in that, S2 includes: extracting all growth stages currently existing in the toad breeding shed based on growth stage information, and establishing a set of coexisting growth stages; obtaining the upper and lower bounds of the requirements for air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in the water for each growth stage in the set of coexisting growth stages; comparing the requirement intervals of all growth stages in the set of coexisting growth stages for each environmental parameter dimension, identifying requirement intervals that do not overlap, and determining the parameter range defined by the requirement intervals that do not overlap as the requirement incompatible intervals in the environmental parameter dimension; traversing each breeding area, and marking breeding areas where the collected value of any environmental parameter falls into the requirement incompatible intervals in the environmental parameter dimension as conflict breeding areas.

5. The method for controlling the toad farming environment based on big data according to claim 4, characterized in that, Obtain the upper and lower bounds of air temperature requirements, air humidity requirements, water temperature requirements, light intensity requirements, and dissolved oxygen content requirements for each growth stage in the coexisting growth stage set under the conditions of breeding density.

6. The method for environmental management of toad farming based on big data according to claim 1, characterized in that, S3 includes: For each conflict breeding area, determining the optimal values ​​for air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content from the upper and lower bounds of the demand for the growth stage of the conflict breeding area; calculating the absolute values ​​of the differences between the collected air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content and their corresponding optimal values ​​as deviations; obtaining the topological connection diagram of the environmental regulation pipeline in the toad breeding shed; identifying conflict breeding area pairs that share the same environmental regulation pipeline trunk; obtaining the spatial adjacency distance between conflict breeding areas; marking the regulation interference degree between conflict breeding area pairs that share the same environmental regulation pipeline trunk and whose spatial adjacency distance is lower than a preset adjacency threshold as strong interference; and marking the regulation interference degree between other conflict breeding area pairs as weak interference.

7. The method for managing the toad farming environment based on big data according to claim 1, characterized in that, S4 includes: extracting conflict aquaculture zone pairs with strong interference; classifying the conflict aquaculture zones involved in the strong interference pairs into a constrained conflict set; classifying the remaining conflict aquaculture zones into an unconstrained conflict set; obtaining the physiological response elasticity coefficient and marginal benefit coefficient of each growth stage to air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in water; calculating the ratio of the physiological response elasticity coefficient to the marginal benefit coefficient as the marginal physiological benefit elasticity ratio; sorting the growth stages in the coexisting growth stage set from low to high according to the marginal physiological benefit elasticity ratio to generate an inter-stage resource competition ranking; directly setting the environmental parameter control target values ​​of the conflict aquaculture zones in each unconstrained conflict set to the optimal value of the demand range of the growth stage in which the conflict aquaculture zone is located; for the conflict aquaculture zones in each constrained conflict set, solving step by step according to the inter-stage resource competition ranking, using the upper limit of the released environmental regulation resources as a constraint, and sequentially determining the environmental parameter control target values ​​of each conflict aquaculture zone.

8. The method for managing the toad farming environment based on big data according to claim 7, characterized in that, The physiological response elasticity coefficient and marginal benefit coefficient of each growth stage to air temperature, air humidity, water temperature, light intensity and dissolved oxygen content in water were obtained. The physiological response elasticity coefficient is the rate of change of toad venom production caused by a unit change in environmental parameters, and the marginal benefit coefficient is the increase in toad venom production caused by a unit input of environmental parameter adjustment resources.

9. A method for managing the toad farming environment based on big data according to claim 1, characterized in that, S5 includes: The environmental parameter control target values ​​for each conflict aquaculture zone are calculated by subtracting them from the real-time collected air temperature, air humidity, water temperature, light intensity, and dissolved oxygen content in the conflict aquaculture zone to obtain the environmental parameter deviation for each conflict aquaculture zone. Based on the environmental parameter deviation and the preset control cycle, control signals are generated. The control signals include start / stop commands for ventilation equipment, start / stop commands for spray equipment, adjustment commands for shading equipment, power commands for heating equipment, and flow commands for water exchange equipment. The control signals are sent to the corresponding environmental control equipment in each conflict aquaculture zone, driving the environmental control equipment to independently perform environmental control actions within the conflict aquaculture zone, thereby achieving zoned control between conflict aquaculture zones.

10. A big data-based toad farming environment management system, used to implement the big data-based toad farming environment management method according to any one of claims 1-9, characterized in that, Includes the following modules: The parameter acquisition module is used to collect environmental parameters from multiple breeding areas within the toad breeding shed and obtain information on the current growth stage of toads in each breeding area. The aquaculture zone identification module is used to determine the set of coexisting growth stages based on growth stage information, and to determine the incompatible demand interval of the set of coexisting growth stages in each environmental parameter dimension according to the demand interval of each growth stage for environmental parameters. Aquaculture zones whose environmental parameters fall into the incompatible demand interval are marked as conflict aquaculture zones. The interference calculation module is used to calculate the deviation between the environmental parameters of each conflicting aquaculture zone and the optimal value of the demand range of its growth stage, and to determine the regulation interference degree of each pair of conflicting aquaculture zones based on the sharing of environmental regulation pipelines and spatial adjacency between conflicting aquaculture zones. The target value solving module is used to calculate the marginal physiological benefit elasticity ratio based on the physiological response elasticity and marginal benefit of each growth stage to environmental parameters, under the constraint that the regulation interference degree does not exceed the preset pipeline crosstalk allowable value. Based on the marginal physiological benefit elasticity ratio, the module generates the inter-stage resource competition ranking, releases environmental regulation resources step by step according to the inter-stage resource competition ranking, and obtains the environmental parameter regulation target value of each conflict aquaculture area. The zone control module is used to generate control signals based on the target values ​​of environmental parameters in each conflicting aquaculture zone, and drive the environmental regulation equipment in the corresponding aquaculture zone to perform zone control.

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