Automated smart farming system that combines monitoring data with the environment

Abstract

The present invention relates to the field of automatic control technology, in particular to an automatic intelligent breeding system combining monitoring data with the environment, comprising: a breeding monitoring module, which monitors the current behavior of breeding animals in a breeding area and the current work of different regulating devices; an environmental acquisition module, which is used to control the acquisition device to collect corresponding environmental parameters in the breeding area; an environmental comparison module, which is used to compare the collected environmental parameters with corresponding preset parameters to determine a first difference; an auxiliary factor acquisition module, which obtains environmental auxiliary factors according to monitoring results, and obtains the device adjustment factor of each regulating device based on the monitoring results; an instruction acquisition module, which calls and optimizes the first adjustment instruction matching the first difference to obtain a second adjustment instruction; and an equipment control module, which controls the corresponding adjustment device to perform corresponding automatic adjustment according to the second adjustment instruction, and adjusts the breeding environment of the breeding area. The reliability of environmental adjustment can be guaranteed, and a better living environment can be provided.

Description

Technical Field

[0001] The present invention relates to the field of automated control technology, and in particular to an automated intelligent farming system that combines monitoring data with the environment. Background Art

[0002] In the traditional breeding process, human participation is required. For example, a temperature measuring instrument is set in the breeding area, and then human observation of the temperature measuring instrument is used to determine whether the fan needs to be turned on for cooling. The fan also needs human operation to turn on. Due to uncontrollable human factors, there may be untimely temperature observation, untimely fan start-up and untimely fan shutdown, which makes the environmental regulation of the breeding area unreliable. Therefore, relevant intelligent means are added to the process of human participation in environmental regulation. For example, different temperature sensors, humidity sensors, environmental detection equipment and various instruments are set to monitor the current breeding area and perform various intelligent adjustments to reduce the unreliable factors of human participation. However, there is no systematic supporting intelligent monitoring means in the prior art.

[0003] Therefore, the present invention proposes an automated intelligent farming system that combines monitoring data with the environment. Summary of the invention

[0004] The present invention provides an automated intelligent farming system that combines monitoring data with the environment. By automatically collecting environmental parameters and comparing them with standards, it can effectively realize intelligent adjustment of the farming area environment. By combining with different monitoring results, it can optimize the adjustment instructions, which can further ensure the reliability of environmental adjustment and facilitate providing a better living environment.

[0005] The present invention provides an automated intelligent farming system that combines monitoring data with the environment, including:

[0006] A breeding monitoring module, which performs a first monitoring of the current behavior of the breeding animals in the breeding area, and a second monitoring of the current operation of different regulating equipment in the breeding area;

[0007] Environmental collection module, used to control the collection equipment to collect the corresponding environmental parameters in the breeding area;

[0008] An environment comparison module, used to compare the collected environment parameters with corresponding preset parameters to determine a first difference;

[0009] an auxiliary factor acquisition module, which acquires the environmental auxiliary factor according to the first monitoring result, and acquires the device adjustment factor of each adjustment device based on the second monitoring result;

[0010] an instruction acquisition module, which retrieves a first adjustment instruction matching the first difference based on an adjustment database, and optimizes the first adjustment instruction based on the environmental auxiliary factor and the equipment adjustment factor to obtain a second adjustment instruction;

[0011] The equipment control module controls the regulating equipment to perform corresponding automatic regulation according to the second regulation instruction, so as to adjust the breeding environment of the breeding area.

[0012] Preferably, the environment acquisition module includes:

[0013] A temperature collection device, used to control the operation of a temperature sensor pre-set in the breeding area and collect temperature parameters of the breeding area;

[0014] A humidity collection device, used to control the humidity sensor pre-set in the breeding area to work and collect humidity parameters of the breeding area;

[0015] The parameter acquisition unit obtains the environmental parameter based on the humidity parameter and the temperature parameter.

[0016] Preferably, the environment comparison module includes:

[0017] A first comparison unit compares the temperature parameter with a preset temperature of the breeding area to obtain a temperature difference parameter;

[0018] A second comparison unit compares the humidity parameter with a preset humidity of the breeding area to obtain a humidity difference parameter;

[0019] The humidity difference parameter and the temperature difference parameter are first differences.

[0020] Preferably, the auxiliary factor acquisition module includes:

[0021] a behavior acquisition unit, configured to acquire the current behavior of each farmed animal in the breeding area according to the first monitoring result;

[0022] A vector construction unit, used to construct a behavior vector for each current behavior;

[0023] A label setting unit, which pre-analyzes the behavior vector based on a behavior analysis model, obtains a behavior state, sets a state label, and prominently displays the location of the farmed animal;

[0024] A behavior map acquisition unit, based on the significant display results of all labels, obtains a significant behavior map of the breeding area;

[0025] A label line construction unit, which obtains label types based on the saliency behavior graph, and determines the number of labels and setting positions of each label, thereby constructing a same-label line;

[0026] A line classification unit, used to classify the same-labeled lines and determine the representativeness of the behavior of each type of labeled line;

[0027] an activity state matching unit, which matches the corresponding animal activity state from the behavior-activity state database based on each behavior representativeness;

[0028] The factor matching unit divides the activity status of the animal according to the activity range, determines the activity category, and matches the environmental auxiliary factors based on the activity-environmental factor database.

[0029] Preferably, the auxiliary factor acquisition module further includes:

[0030] a contribution coefficient determination unit, which obtains a set of working parameters of different regulating devices in the breeding area within a preset time period according to the second monitoring result, and determines a device environment contribution coefficient of the corresponding regulating device based on the corresponding regulating device and the installation position of the breeding area;

[0031] An array construction unit constructs a coefficient array based on all equipment environment contribution coefficients and equipment serial number sequence;

[0032] An array comparison unit, used for comparing the coefficient array with a standard array to obtain a difference array;

[0033] A difference acquisition unit, used to acquire a difference coefficient corresponding to the regulating device, and combine the difference coefficient with the difference array to obtain an auxiliary difference, and acquire a set difference between a working parameter set of the corresponding regulating device and a standard parameter set;

[0034] The adjustment factor retrieving unit retrieves the device adjustment factor of the corresponding adjustment device from the difference-factor database based on the auxiliary difference and the set difference.

[0035] Preferably, the instruction acquisition module includes:

[0036] A first difference matching unit, configured to obtain a temperature difference parameter in the first difference, and obtain a first instruction set by matching from the adjustment database;

[0037] a second difference matching unit, configured to obtain a humidity difference parameter in the first difference, and obtain a second instruction set by matching the first instruction set;

[0038] an instruction judging unit, configured to judge whether the number of instructions in the second instruction set is one, and if so, take the only instruction as the first adjustment instruction;

[0039] a difference curve construction unit, which, when the number of instructions is not one, obtains a temperature difference parameter within a preset time period and constructs a temperature difference curve, obtains a humidity difference parameter within a preset time period and constructs a humidity difference curve;

[0040] a temperature difference acquisition unit, configured to fit the temperature difference curve, acquire a first temperature difference, and acquire a maximum temperature difference and a minimum temperature difference in the temperature difference curve;

[0041] A humidity difference acquisition unit, used for fitting the humidity difference curve, acquiring a first humidity difference, and acquiring a maximum humidity difference and a minimum humidity difference in the humidity difference curve;

[0042] The coefficient calculation unit is used to calculate the humidity difference adjustment coefficient and the temperature difference adjustment coefficient. The calculation formula is as follows:

[0043]

[0044]

[0045] Among them, Y1 represents the humidity difference coefficient to be adjusted; Y2 represents the temperature difference coefficient to be adjusted; Indicates the maximum humidity difference; Indicates the minimum humidity difference; first humidity difference; Indicates the maximum temperature difference; Indicates the minimum temperature difference; The first temperature difference; ln() represents the fine-tuning function;

[0046] The instruction screening unit screens a unique instruction from the second instruction set as a first adjustment instruction based on the humidity difference coefficient to be adjusted and the temperature difference coefficient to be adjusted.

[0047] Preferably, the instruction acquisition module further includes:

[0048] an adjustable parameter determination unit, which determines, based on a factor-adjustment database, a first adjustable parameter that matches the environmental auxiliary factor and a second adjustable parameter that matches the device adjustment factor;

[0049] a matching relationship establishing unit, which parses the first adjustment instruction based on an instruction parsing model to obtain parsing parameters, and establishes a matching relationship between the parsing parameters and the first adjustable parameters and the second adjustable parameters;

[0050] A relationship screening unit, screening a first relationship with reliability based on the matchable relationship;

[0051] The instruction optimization unit is used to optimize and adjust the corresponding parsing parameters according to the adjustable parameters in the first relationship, and reconstruct the second adjustment instruction according to all the adjusted parameters.

[0052] Preferably, the device control module includes:

[0053] Extracting a sub-instruction matching a device model of each regulating device from the second regulating instruction;

[0054] Control the automatic adjustment of the corresponding adjustment equipment according to the sub-instructions;

[0055] Among them, the automatic adjustment includes: increasing the operating power of the corresponding adjustment equipment, reducing the operating power of the corresponding adjustment equipment, controlling the corresponding adjustment equipment to be turned off, or controlling the corresponding adjustment equipment to be turned on.

[0056] Preferably, the environmental parameters are related to the temperature and humidity of the farm.

[0057] Preferably, the regulating device is a fan device.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] By automatically collecting environmental parameters and comparing them with standards, the intelligent adjustment of the breeding area environment can be effectively realized. By combining with different monitoring results, the adjustment instructions can be optimized, which can further ensure the reliability of environmental adjustment and provide a better living environment.

[0060] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0061] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0063] Figure 1 It is a structural diagram of an automated intelligent farming system combining monitoring data with the environment in an embodiment of the present invention;

[0064] Figure 2 is a significant behavior diagram in an embodiment of the present invention;

[0065] Figure 3is a structural diagram of an auxiliary factor acquisition module in an embodiment of the present invention;

[0066] Figure 4 Another structural diagram of the auxiliary factor acquisition module in an embodiment of the present invention;

[0067] Figure 5 4 is a structural diagram of an instruction acquisition module in an embodiment of the present invention. DETAILED DESCRIPTION

[0068] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0069] The present invention provides an automated intelligent farming system that combines monitoring data with the environment, such as Figure 1 As shown, including:

[0070] A breeding monitoring module, which performs a first monitoring of the current behavior of the breeding animals in the breeding area, and a second monitoring of the current operation of different regulating equipment in the breeding area;

[0071] Environmental collection module, used to control the collection equipment to collect the corresponding environmental parameters in the breeding area;

[0072] An environment comparison module, used to compare the collected environment parameters with corresponding preset parameters to determine a first difference;

[0073] an auxiliary factor acquisition module, which acquires the environmental auxiliary factor according to the first monitoring result, and acquires the device adjustment factor of each adjustment device based on the second monitoring result;

[0074] an instruction acquisition module, which retrieves a first adjustment instruction matching the first difference based on an adjustment database, and optimizes the first adjustment instruction based on the environmental auxiliary factor and the equipment adjustment factor to obtain a second adjustment instruction;

[0075] The equipment control module controls the regulating equipment to perform corresponding automatic regulation according to the second regulation instruction, so as to adjust the breeding environment of the breeding area.

[0076] Preferably, the environmental parameters are related to the temperature and humidity of the farm.

[0077] Preferably, the regulating device is a fan device.

[0078] In this embodiment, the farmed animals may be cattle, sheep, etc.

[0079] In this embodiment, the first monitoring is the monitoring of animal behavior, and the second monitoring is the monitoring of equipment operation.

[0080] In this embodiment, the preset parameter is pre-set, for example, the preset temperature parameter is 24 degrees Celsius. At this time, the actual temperature is 25 degrees Celsius, and the corresponding first difference is 1 degree Celsius.

[0081] In this embodiment, the environmental cofactor is determined based on the behavioral state of the animal. The behavioral state reflected at different temperatures is different, so the environmental cofactor is obtained.

[0082] In this embodiment, the device adjustment factor is determined based on the device operating conditions, providing a basis for subsequent instruction optimization.

[0083] In this embodiment, the automated adjustment work refers to the adjustment of temperature, humidity, etc.

[0084] The beneficial effect of the above technical solution is: by comparing the automatically collected environmental parameters with the standard parameters, the intelligent adjustment of the breeding area environment can be realized. By combining with different monitoring results, the adjustment instructions can be optimized, which can further ensure the reliability of environmental adjustment and facilitate the provision of a good living environment.

[0085] The present invention provides an automated intelligent farming system that combines monitoring data with the environment, wherein the environment acquisition module comprises:

[0086] A temperature collection device, used to control the operation of a temperature sensor pre-set in the breeding area and collect temperature parameters of the breeding area;

[0087] A humidity collection device, used to control the humidity sensor pre-set in the breeding area to work and collect humidity parameters of the breeding area;

[0088] The parameter acquisition unit obtains the environmental parameter based on the humidity parameter and the temperature parameter.

[0089] The beneficial effect of the above technical solution is: by collecting parameters through temperature sensors and humidity sensors, it is easy to obtain environmental parameters and provide a basis for subsequent environmental adjustment.

[0090] The present invention provides an automated intelligent farming system combining monitoring data with the environment, wherein the environment comparison module comprises:

[0091] A first comparison unit compares the temperature parameter with a preset temperature of the breeding area to obtain a temperature difference parameter;

[0092] A second comparison unit compares the humidity parameter with a preset humidity of the breeding area to obtain a humidity difference parameter;

[0093] The humidity difference parameter and the temperature difference parameter are first differences.

[0094] In this embodiment, the first difference refers to a temperature difference parameter or a humidity difference parameter.

[0095] The beneficial effect of the above technical solution is that the first difference can be easily obtained by performing temperature comparison and humidity comparison.

[0096] The present invention provides an automated intelligent farming system combining monitoring data with the environment, wherein the auxiliary factor acquisition module is as follows: Figure 3 As shown, including:

[0097] a behavior acquisition unit, configured to acquire the current behavior of each farmed animal in the breeding area according to the first monitoring result;

[0098] A vector construction unit, used to construct a behavior vector for each current behavior;

[0099] A label setting unit, which pre-analyzes the behavior vector based on a behavior analysis model, obtains a behavior state, sets a state label, and prominently displays the location of the farmed animal;

[0100] A behavior map acquisition unit, based on the significant display results of all labels, obtains a significant behavior map of the breeding area;

[0101] A label line construction unit, which obtains label types based on the saliency behavior graph, and determines the number of labels and setting positions of each label, thereby constructing a same-label line;

[0102] A line classification unit, used to classify the same-labeled lines and determine the representativeness of the behavior of each type of labeled line;

[0103] an activity state matching unit, which matches the corresponding animal activity state from the behavior-activity state database based on each behavior representativeness;

[0104] The factor matching unit divides the activity status of the animal according to the activity range, determines the activity category, and matches the environmental auxiliary factors based on the activity-environmental factor database.

[0105] In this embodiment, the current behavior acquires postures from different parts to construct a behavior vector, such as the head, legs, body, etc.

[0106] In this embodiment, the behavior analysis model is trained based on different postures and behavior states matching the postures, so as to obtain the behavior state of the behavior vector.

[0107] In this embodiment, if Figure 2 As shown, 01, 02, and 03 are different status labels, and Figure 2 This is a significant behavior map of the breeding area, and different lines correspond to different label lines.

[0108] The representativeness of the behavior of each type of label line is determined separately, including the following calculation formula:

[0109]

[0110] Among them, m1 represents the number of label lines in the corresponding class; m2 represents the number of labels in the corresponding label line, and m1 and m2 are variables; represents the significance value of the j2th label in the j1th category; represents the weight value of the j2th label in the j1th category, Less than 1.

[0111] In this embodiment, the behavior-activity status database includes different behavior representations and activity statuses matching the behavior representations, thereby obtaining the activity status of the animal.

[0112] In this embodiment, the activity range is preset, for example, corresponding ranges of extremely inactive state, slightly active state, generally active state, very active state, etc., and then the activity states are divided to obtain major activity categories.

[0113] In this embodiment, the activity-environmental factor database includes different activity categories and environmental auxiliary factors corresponding to the categories, for example, fine-tuning of temperature is performed on the basis of determining the adjustment.

[0114] In this embodiment, line classification refers to classifying lines with similar significance labeling results into one category.

[0115] The beneficial effects of the above technical solution are: analyzing the current behavior through monitoring results and constructing a behavior vector, determining the label based on the model, and then constructing a significant behavior graph based on the significant results, and by constructing label lines and classifying the lines, it is easy to calculate the representativeness of the behavior and effectively obtain environmental auxiliary factors.

[0116] The present invention provides an automated intelligent farming system combining monitoring data with the environment, wherein the auxiliary factor acquisition module is as follows: Figure 4 As shown, it also includes:

[0117] a contribution coefficient determination unit, which obtains a set of working parameters of different regulating devices in the breeding area within a preset time period according to the second monitoring result, and determines a device environment contribution coefficient of the corresponding regulating device based on the corresponding regulating device and the installation position of the breeding area;

[0118] An array construction unit constructs a coefficient array based on all equipment environment contribution coefficients and equipment serial number sequence;

[0119] An array comparison unit, used for comparing the coefficient array with a standard array to obtain a difference array;

[0120] A difference acquisition unit, used to acquire a difference coefficient corresponding to the regulating device, and combine the difference coefficient with the difference array to obtain an auxiliary difference, and acquire a set difference between a working parameter set of the corresponding regulating device and a standard parameter set;

[0121] The adjustment factor retrieving unit retrieves the device adjustment factor of the corresponding adjustment device from the difference-factor database based on the auxiliary difference and the set difference.

[0122] In this embodiment, the difference-factor database includes different auxiliary differences and collective difference combinations, and also includes matching device adjustment factors, where the device adjustment factors are fine-tuning factors related to temperature and humidity.

[0123] In this embodiment, the second monitoring result obtains a set of working parameters of different adjustment devices, such as a set of working parameters within 1 minute including the current time point.

[0124] The calculation of equipment environment contribution coefficient is as follows:

[0125]

[0126] in, Indicates the position weight of the installation position of the corresponding regulating device; Indicates the number of working parameters involved in the corresponding adjustment equipment; represents the parameter weight of the j3th operating parameter of the corresponding regulating device; Indicates the current value of the j3th working parameter of the corresponding regulating device; Indicates the standard value of the j3rd operating parameter of the corresponding regulating device.

[0127] In this embodiment, according to the sequence number, the coefficient array finally obtained is ,in, Represents the contribution coefficient of the N11th regulating device.

[0128] In this embodiment, the standard array is pre-set, for example: , subtract the coefficient array from the standard array to get the difference array ,and It can be regarded as the difference coefficient.

[0129] In this embodiment, the auxiliary difference determines the difference coefficient based on the difference array, for example, the difference coefficient is determined relative to a difference in the difference array, based on whether the difference array is a transition difference or a normal difference.

[0130] In this embodiment, the set difference is m3 The differences constituted.

[0131] The beneficial effects of the above technical solution are: by obtaining the working parameter set and the installation location, the equipment environment contribution coefficient is determined, and by constructing a coefficient array to obtain different differences and set difference combinations, the equipment adjustment factor is obtained, which provides an effective basis for subsequent environmental adjustment and ensures the reliability of environmental adjustment.

[0132] The present invention provides an automated intelligent farming system that combines monitoring data with the environment, wherein the instruction acquisition module is as follows: Figure 5 As shown, including:

[0133] A first difference matching unit, configured to obtain a temperature difference parameter in the first difference, and obtain a first instruction set by matching from the adjustment database;

[0134] a second difference matching unit, configured to obtain a humidity difference parameter in the first difference, and obtain a second instruction set by matching the first instruction set;

[0135] an instruction judging unit, configured to judge whether the number of instructions in the second instruction set is one, and if so, take the only instruction as the first adjustment instruction;

[0136] a difference curve construction unit, which, when the number of instructions is not one, obtains a temperature difference parameter within a preset time period and constructs a temperature difference curve, obtains a humidity difference parameter within a preset time period and constructs a humidity difference curve;

[0137] a temperature difference acquisition unit, configured to fit the temperature difference curve, acquire a first temperature difference, and acquire a maximum temperature difference and a minimum temperature difference in the temperature difference curve;

[0138] A humidity difference acquisition unit, used for fitting the humidity difference curve, acquiring a first humidity difference, and acquiring a maximum humidity difference and a minimum humidity difference in the humidity difference curve;

[0139] The coefficient calculation unit is used to calculate the humidity difference adjustment coefficient and the temperature difference adjustment coefficient. The calculation formula is as follows:

[0140]

[0141]

[0142] Among them, Y1 represents the humidity difference coefficient to be adjusted; Y2 represents the temperature difference coefficient to be adjusted; Indicates the maximum humidity difference; Indicates the minimum humidity difference; first humidity difference; Indicates the maximum temperature difference; Indicates the minimum temperature difference; The first temperature difference; ln() represents the fine-tuning function;

[0143] The instruction screening unit screens a unique instruction from the second instruction set as a first adjustment instruction based on the humidity difference coefficient to be adjusted and the temperature difference coefficient to be adjusted.

[0144] In this embodiment, the first instruction set is obtained according to the temperature difference parameter, such as: adjusting to 24 degrees Celsius, and the humidity can be 65, 89, 45, etc. The second instruction set, such as: adjusting to 24 degrees Celsius and specifying the humidity to be 65, is 1 instruction at this time and serves as the only instruction.

[0145] If there are multiple instructions, the required different values ​​are obtained by fitting the temperature difference curve and the humidity difference curve within the preset time period.

[0146] In this embodiment, the calculation of Y1 and Y2 is for comparing the importance of temperature and humidity, that is, the importance of temperature and humidity is determined by the size of Y1B1 and Y2B2.

[0147] B1 and B2 represent standard conversion factors for standard comparison.

[0148] For example, there are two instructions, Instruction 1 and Instruction 2. In this case, Instruction 1 is to adjust the temperature to 24 degrees Celsius, the humidity to a1, and tends to adjust the temperature and then the humidity. Instruction 2 is to adjust the temperature to 24 degrees Celsius, the humidity to a1, and tends to adjust the humidity and then the temperature.

[0149] Therefore, by comparing the sizes of Y1B1 and Y2B2, a unique instruction can be effectively screened out.

[0150] The beneficial effect of the above technical solution is: by matching instructions with temperature difference parameters and humidity difference parameters, it is convenient to effectively adjust the environment. During the adjustment process, different values ​​of temperature and humidity are obtained by curve fitting, and the corresponding coefficients to be adjusted are calculated, thereby achieving unique acquisition of instructions, providing a precise basis for adjusting the environment, ensuring precise adjustment, and further improving the reliability of adjustment.

[0151] The present invention provides an automated intelligent farming system that combines monitoring data with the environment, wherein the instruction acquisition module further comprises:

[0152] an adjustable parameter determination unit, which determines, based on a factor-adjustment database, a first adjustable parameter that matches the environmental auxiliary factor and a second adjustable parameter that matches the device adjustment factor;

[0153] a matching relationship establishing unit, which parses the first adjustment instruction based on an instruction parsing model to obtain parsing parameters, and establishes a matching relationship between the parsing parameters and the first adjustable parameters and the second adjustable parameters;

[0154] A relationship screening unit, screening a first relationship with reliability based on the matchable relationship;

[0155] The instruction optimization unit is used to optimize and adjust the corresponding parsing parameters according to the adjustable parameters in the first relationship, and reconstruct the second adjustment instruction according to all the adjusted parameters.

[0156] In this embodiment, the factor-adjustment database includes different environmental auxiliary factors, equipment adjustment factors and matching adjustable parameters.

[0157] In this embodiment, the instruction parsing model obtains parsing parameters based on different adjustment instructions and parsing results corresponding to the instructions.

[0158] For example: there are analytical parameters 1, 2, and 3, first adjustable parameters 1 and 2, and second adjustable parameters 1 and 2. The analytical parameter 1 has a relationship with the first adjustable parameters 1 and 2, the analytical parameter 2 has a relationship with the second adjustable parameter 1, and the analytical parameter 3 has a relationship with the first adjustable parameter 1 and the second adjustable parameter 2.

[0159] The first relationship screened is: analysis parameter 1 and first adjustable parameters 1 and 2, analysis parameter 3 and first adjustable parameter 1 and second adjustable parameter 2.

[0160] In this embodiment, the adjustable parameters of the first relationship are first adjustable parameters 1 and 2 and second adjustable parameter 2. The parsing parameters are optimized based on the adjustable parameters, such as adjusting the parameter values.

[0161] In this embodiment, based on the adjusted parameters and the parameters that do not need to be adjusted, the second adjustment instruction can be obtained again to ensure the accuracy of the adjustment.

[0162] The beneficial effect of the above technical solution is: by determining the adjustable parameters of different factors, and parsing the instructions and matching the relationships based on the model, the final parameters can be effectively screened to optimize the parsing parameters, ensure the accuracy of the instructions, and further ensure the reliability of the environmental adjustment.

[0163] The present invention provides an automated intelligent farming system that combines monitoring data with the environment, wherein the equipment control module comprises:

[0164] Extracting a sub-instruction matching a device model of each regulating device from the second regulating instruction;

[0165] Control the automatic adjustment of the corresponding adjustment equipment according to the sub-instructions;

[0166] Among them, the automatic adjustment includes: increasing the operating power of the corresponding adjustment equipment, reducing the operating power of the corresponding adjustment equipment, controlling the corresponding adjustment equipment to be turned off, or controlling the corresponding adjustment equipment to be turned on.

[0167] The beneficial effect of the above technical solution is: by matching the device model with the instruction, the device is adjusted to achieve effective adjustment of the environment and ensure the reliability of the adjustment.

[0168] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An automated intelligent farming system combining monitoring data with the environment, characterized in that: include: A farming monitoring module, which performs a first monitoring of the current behavior of the farmed animals in the farming area, and a second monitoring of the current operation of different regulating equipment in the farming area; Environmental collection module, used to control the collection equipment to collect the corresponding environmental parameters in the breeding area; An environment comparison module, used to compare the collected environment parameters with corresponding preset parameters to determine a first difference; an auxiliary factor acquisition module, which acquires the environmental auxiliary factor according to the first monitoring result, and acquires the device adjustment factor of each adjustment device based on the second monitoring result; an instruction acquisition module, which retrieves a first adjustment instruction matching the first difference based on an adjustment database, and optimizes the first adjustment instruction based on the environmental auxiliary factor and the equipment adjustment factor to obtain a second adjustment instruction; an equipment control module, controlling the regulating equipment to perform corresponding automatic regulation according to the second regulation instruction, so as to adjust the breeding environment of the breeding area; Wherein, the instruction acquisition module includes: A first difference matching unit, configured to obtain a temperature difference parameter in the first difference, and obtain a first instruction set by matching from the adjustment database; a second difference matching unit, configured to obtain a humidity difference parameter in the first difference, and obtain a second instruction set by matching the first instruction set; an instruction judging unit, configured to judge whether the number of instructions in the second instruction set is one, and if so, take the only instruction as the first adjustment instruction; a difference curve construction unit, which, when the number of instructions is not one, obtains a temperature difference parameter within a preset time period and constructs a temperature difference curve, obtains a humidity difference parameter within a preset time period and constructs a humidity difference curve; a temperature difference acquisition unit, configured to fit the temperature difference curve, acquire a first temperature difference, and acquire a maximum temperature difference and a minimum temperature difference in the temperature difference curve; A humidity difference acquisition unit, used for fitting the humidity difference curve, acquiring a first humidity difference, and acquiring a maximum humidity difference and a minimum humidity difference in the humidity difference curve; The coefficient calculation unit is used to calculate the humidity difference adjustment coefficient and the temperature difference adjustment coefficient. The calculation formula is as follows: ; ; Among them, Y1 represents the humidity difference coefficient to be adjusted; Y2 represents the temperature difference coefficient to be adjusted; Indicates the maximum humidity difference; Indicates the minimum humidity difference; first humidity difference; Indicates the maximum temperature difference; Indicates the minimum temperature difference; The first temperature difference; ln() represents the fine-tuning function; The instruction screening unit screens a unique instruction from the second instruction set as a first adjustment instruction based on the humidity difference coefficient to be adjusted and the temperature difference coefficient to be adjusted.

2. The automated intelligent farming system combining monitoring data and environment as claimed in claim 1, characterized in that: The environment acquisition module includes: A temperature collection device, used to control the operation of a temperature sensor pre-set in the breeding area and collect temperature parameters of the breeding area; A humidity collection device, used to control the humidity sensor pre-set in the breeding area to work and collect humidity parameters of the breeding area; The parameter acquisition unit obtains the environmental parameter based on the humidity parameter and the temperature parameter.

3. The automated intelligent farming system combining monitoring data and environment as claimed in claim 2, characterized in that: The environment comparison module comprises: A first comparison unit compares the temperature parameter with a preset temperature of the breeding area to obtain a temperature difference parameter; A second comparison unit compares the humidity parameter with a preset humidity of the breeding area to obtain a humidity difference parameter; The humidity difference parameter and the temperature difference parameter are first differences.

4. The automated intelligent farming system combining monitoring data and environment as claimed in claim 1, characterized in that: The auxiliary factor acquisition module comprises: a behavior acquisition unit, configured to acquire the current behavior of each farmed animal in the breeding area according to the first monitoring result; A vector construction unit, used to construct a behavior vector for each current behavior; A label setting unit, which pre-analyzes the behavior vector based on a behavior analysis model, obtains a behavior state, sets a state label, and prominently displays the location of the farmed animal; A behavior map acquisition unit, based on the significant display results of all labels, obtains a significant behavior map of the breeding area; A label line construction unit, which obtains label types based on the saliency behavior graph, and determines the number of labels and setting positions of each label, thereby constructing a same-label line; A line classification unit, used to classify the same-labeled lines and determine the representativeness of the behavior of each type of labeled line; an activity state matching unit, which matches the corresponding animal activity state from the behavior-activity state database based on each behavior representativeness; The factor matching unit divides the activity status of the animal according to the activity range, determines the activity category, and matches the environmental auxiliary factors based on the activity-environmental factor database.

5. The automated intelligent farming system combining monitoring data and environment as claimed in claim 1, characterized in that: The auxiliary factor acquisition module also includes: a contribution coefficient determination unit, which obtains a set of working parameters of different regulating devices in the breeding area within a preset time period according to the second monitoring result, and determines a device environment contribution coefficient of the corresponding regulating device based on the corresponding regulating device and the installation position of the breeding area; An array construction unit constructs a coefficient array based on all equipment environment contribution coefficients and equipment serial number sequence; An array comparison unit, used for comparing the coefficient array with a standard array to obtain a difference array; A difference acquisition unit, used to acquire a difference coefficient corresponding to the regulating device, and combine the difference coefficient with the difference array to obtain an auxiliary difference, and acquire a set difference between a working parameter set of the corresponding regulating device and a standard parameter set; The adjustment factor retrieving unit retrieves the device adjustment factor of the corresponding adjustment device from the difference-factor database based on the auxiliary difference and the set difference.

6. The automated intelligent farming system combining monitoring data and environment as claimed in claim 1, characterized in that: The instruction acquisition module also includes: an adjustable parameter determination unit, which determines, based on a factor-adjustment database, a first adjustable parameter that matches the environmental auxiliary factor and a second adjustable parameter that matches the device adjustment factor; a matching relationship establishing unit, which parses the first adjustment instruction based on an instruction parsing model to obtain parsing parameters, and establishes a matching relationship between the parsing parameters and the first adjustable parameters and the second adjustable parameters; A relationship screening unit, screening a first relationship with reliability based on the matching relationship; The instruction optimization unit is used to optimize and adjust the corresponding parsing parameters according to the adjustable parameters in the first relationship, and reconstruct the second adjustment instruction according to all the adjusted parameters.

7. The automated intelligent farming system combining monitoring data and environment as claimed in claim 1, characterized in that: The device control module comprises: Extracting a sub-instruction matching a device model of each regulating device from the second regulating instruction; Control the automatic adjustment of the corresponding adjustment equipment according to the sub-instructions; Among them, the automatic adjustment includes: increasing the operating power of the corresponding adjustment equipment, reducing the operating power of the corresponding adjustment equipment, controlling the corresponding adjustment equipment to be turned off, or controlling the corresponding adjustment equipment to be turned on.

8. The automated intelligent farming system combining monitoring data and environment as claimed in claim 1, characterized in that: The environmental parameters are related to the temperature and humidity of the farm.

9. The automated intelligent farming system combining monitoring data and environment as claimed in claim 1, characterized in that: The regulating device is a fan device.

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