Planting environment control method based on oat planting

Abstract

The invention discloses a planting environment control method based on oat planting, and relates to the technical field of planting environment control. The method comprises the following steps: collecting real-time scene data of oat planting, and judging whether an oat planting environment is changed or not; if so, determining to obtain a control service object of planting environment control; collecting object information of the control service objects, and screening the control service objects to obtain actual control objects; counting parameter adjusting equipment corresponding to all actual control objects, and collecting corresponding parameter application information; main reference information is selected according to the parameter application information, parameter adjusting equipment corresponding to the main reference information is controlled according to the real-time scene data, and main reference data are obtained; and controlling and adjusting other parameter adjusting equipment according to the main reference data and the real-time scene data. According to the invention, the accuracy of planting environment control based on oat planting is improved.

Description

Technical Field

[0001] The present application relates to the technical field of planting environment control, and in particular to a planting environment control method based on oat planting. Background Art

[0002] Oat cultivation-based planting environment control is a technical system that optimizes crop growth conditions by comprehensively regulating soil, water, temperature, light, and biological factors. By using IoT sensors to monitor key indicators such as soil moisture, temperature, light intensity, and carbon dioxide concentration in real time, and adjusting the water-fertilizer ratio and sowing density, the oat growth environment can be significantly optimized. In traditional oat cultivation technology, planting environment control mostly relies on manual experience management and lacks systematic monitoring and dynamic control mechanisms. Existing technologies either generally adopt a decentralized management model, such as making local adjustments through a single indicator, and fail to integrate the collaborative optimization of multi-dimensional environmental parameters. Or, the collaborative control sets the priority of equipment adjustment, and fails to adjust the control of the equipment according to the actual scenario. This results in the inability to provide accurate control solutions according to changes in the planting environment. Summary of the Invention

[0003] The object of the present invention is to provide a planting environment control method based on oat planting to solve the problems raised in the above background technology.

[0004] This application provides a method for controlling the planting environment based on oat planting, which adopts the following technical solutions:

[0005] Collect real-time scene data of oat planting and determine whether the oat planting environment has changed based on the real-time scene data;

[0006] If the oat planting environment changes, the control service object of the adjustment parameter equipment for the planting environment control is confirmed based on the real-time scene data;

[0007] Collect object information of the control service object, and filter the actual control object from the control service objects according to the object information;

[0008] Count all the adjustment parameter devices corresponding to the actual controlled objects and collect the parameter application information of the adjustment parameter devices;

[0009] Selecting primary reference information according to parameter application information, controlling the adjustment parameter device corresponding to the primary reference information according to real-time scene data, and obtaining primary reference data;

[0010] Control and adjust other adjustment parameter devices based on the main reference data and real-time scene data.

[0011] Preferably, if the oat planting environment changes, the step of confirming the control service object of the adjustment parameter device for the planting environment control according to the real-time scene data is specifically as follows:

[0012] Obtain a real-time control plan for the oat planting environment, and extract the control object corresponding to the real-time control plan as the original control object;

[0013] Extract the changed data according to the real-time scene data, and extract the newly added control object as the changed control object according to the changed data and the original control object;

[0014] A control service object is formed based on the changed control object and the original control object.

[0015] Preferably, the step of collecting object information of the control service object and filtering the actual control object from the control service object according to the object information is specifically as follows:

[0016] Collect the overall control objectives of oat planting environment control and determine whether the control service object is related to the overall control objectives;

[0017] Screening and removing control service objects that are not related to the overall control objective to obtain a first control object;

[0018] Determine whether the first controlled object is affected by the control of the parameter adjustment device, filter out the first controlled object that is not affected by the control of the parameter adjustment device, and obtain the second controlled object;

[0019] obtaining individual information of a second control subject, and evaluating a primary impact value of the second control subject on oats based on the individual information;

[0020] obtaining behavioral information of a second controlled object, and evaluating a medium impact value of the second controlled object based on the behavioral information;

[0021] obtaining existence information of a second control object, and evaluating a high-level impact value of the second control object on oats based on the existence information;

[0022] The primary impact value, the medium impact value and the high impact value are integrated to obtain the oat impact value of the control service object, and the actual control object is obtained by screening from the second control objects according to the oat impact value.

[0023] Preferably, the step of determining whether the first controlled object is affected by the control of the parameter adjustment device is specifically:

[0024] determining whether the first controlled object senses the control adjustment of the adjustment parameter device, and if so, collecting the application adjustment range of the adjustment parameter device;

[0025] determining, based on the application adjustment range, whether a behavioral characteristic of the first control object within the application adjustment range is affected;

[0026] If the behavioral characteristics of the first controlled object are not affected, it is determined that the first controlled object is not affected by the control of the parameter adjustment device;

[0027] If the behavior characteristics of the first controlled object are affected, determining whether the change in the behavior characteristics of the first controlled object affects the overall control objective;

[0028] If the overall control target is affected, it is determined that the first controlled object is affected by the control of the adjustment parameter device.

[0029] Preferably, the step of obtaining individual information of the second control object and evaluating the primary impact value of the second control object on oats according to the individual information is specifically as follows:

[0030] Acquire individual information of a second control object, and extract, based on the individual information, required resources of the object and information about environmental changes caused by the individual object to the environment;

[0031] Obtain oat demand resources and oat planting environment, and obtain competitive resources based on the resource intersection of oat demand resources and object demand resources;

[0032] The resource overlap was calculated based on the competing resources and oat demand resources;

[0033] extracting the object resource absorption rate of the second control object for the competing resource according to the individual information;

[0034] Collect the oat resource absorption rate of the competing resources and calculate the absorption rate difference between the target resource absorption rate and the oat resource absorption rate;

[0035] The environmental change information and the environmental similarity of the oat planting environment are compared, and the primary impact value of the second control object on oats is obtained by combining the resource overlap and absorption rate difference.

[0036] Preferably, the step of obtaining the behavior information of the second controlled object and evaluating the medium impact value of the second controlled object according to the behavior information is specifically as follows:

[0037] Determine whether the second control subject has a destructive intention towards oats based on the behavioral information;

[0038] If there is a sense of destruction, the average destruction value of the second control subject on oats is obtained based on the behavioral information extraction as the medium impact value;

[0039] If there is no intention to destroy, then determine whether the second control subject has an intention to protect oats based on the behavior information;

[0040] If there is no protection awareness, the behavior characteristics of the object are extracted based on the behavior information;

[0041] Obtain standard behavioral characteristics for treating oats, and compare the characteristic similarity between the standard behavioral characteristics and the object behavioral characteristics as the autonomous control ability value;

[0042] If there is protection awareness, the autonomous control ability value is the maximum value;

[0043] A correlation curve diagram between the autonomous control capability value of the second control object and the oat impact consequence is established, and the oat impact consequence is obtained as the medium impact value according to the correlation curve diagram.

[0044] Preferably, the step of obtaining the existence information of the second control object and evaluating the higher impact value of the second control object on oats according to the existence information is specifically:

[0045] Acquiring existence information of a second control object, and determining whether the appearance of the second control object is a fixed phenomenon according to the existence information;

[0046] If it is a fixed phenomenon, the average existence duration and average number of existence are extracted based on the existence information;

[0047] The high impact value of the second control object on oats was obtained by combining the average existence duration and the average existence quantity;

[0048] If the appearance of the second control object is not a fixed phenomenon, the appearance frequency of the second control object is counted as a high-level influence value.

[0049] Preferably, the step of selecting main reference information according to parameter application information, and controlling the adjustment parameter device corresponding to the main reference information according to real-time scene data to obtain the main reference data is specifically as follows:

[0050] Collecting service impact information of parameter application information, and obtaining application demand of the parameter application information based on the evaluation of the service impact information;

[0051] Collecting adjustment information of the parameter application information, and obtaining adjustment convenience of the parameter application information based on the evaluation of the adjustment information;

[0052] The control reference degree of parameter application information is obtained by combining the parameter demand degree and adjustment convenience evaluation;

[0053] Select the adjustment parameter device corresponding to the parameter application information with the largest control reference degree as the main reference device, control the adjustment parameter device corresponding to the main reference information according to the real-time scene data, and obtain the real-time adjustment data of the main reference device as the main reference data.

[0054] Preferably, the step of collecting service impact information of the parameter application information and obtaining the application demand of the parameter application information based on the evaluation of the service impact information is specifically as follows:

[0055] Obtain the actual control object covered by the parameter application information as the parameter control object, and compare the oat impact value of the parameter control object to obtain the object weight ratio of the parameter control object;

[0056] The influence degree of the collected parameter application information on the parameter control object is combined with the corresponding object weight ratio to obtain the parameter demand degree of the parameter application information;

[0057] The influence degree of the collected parameter application information on the overall control target is combined with the parameter demand degree to obtain the application demand degree of the parameter application information.

[0058] Preferably, the step of collecting adjustment information of the parameter application information and evaluating the adjustment convenience of the parameter application information according to the adjustment information is specifically as follows:

[0059] The number of actual control objects covered by the statistical parameter application information is recorded as the number of objects;

[0060] Calculate the average adjustment range and average adjustment frequency of the actual control object's parameter application information;

[0061] The number of adjustment parameter devices referenced in the parameter application information adjustment process is counted and recorded as the number of devices;

[0062] The adjustment convenience of parameter application information is obtained by combining the number of objects, average adjustment range, average adjustment frequency and number of devices.

[0063] In summary, this application includes at least one of the following beneficial technical effects:

[0064] 1. Determine whether the oat planting environment has changed based on the real-time scene data of oat planting. If the oat planting environment has changed, the original control object is retrieved according to the real-time control scheme of the oat planting environment, and the real-time scene information is combined to determine whether there is a new control object, and the control service object that needs to be served in the corresponding scene is obtained. The actual control object that needs to be considered for service in the control and adjustment of the planting environment is obtained based on the individual information, behavior information and existence information of the service object. Count the adjustment parameter devices corresponding to all actual control objects, and collect the parameter application information of the adjustment parameter devices. Select the main reference information based on the parameter application information to obtain the corresponding main reference data, and refer to the main reference data to perform overall control and adjustment of the oat planting environment. Switching the main reference basis of the oat planting environment adjustment equipment according to different scenarios can make the control and adjustment scheme of the planting environment more adapted to the actual scenario, thereby improving the accuracy of the planting environment control based on oat planting.

[0065] 2. Screen and remove control service objects that are not related to the overall control objective of oat cultivation environment control. Based on the judgment results of whether the first control object perceives the control adjustment of the adjustment parameter device, whether the behavioral characteristics of the first control object within the application adjustment range are affected, and whether the change in behavioral characteristics affects the overall control objective, further screen and remove control service objects that are not affected by the control of the adjustment parameter device to obtain the second control object. Based on the resource competition, resource overlap, and environmental change impact of the second control object and oats, the primary impact value of the second control object on oats is obtained. Based on the judgment results of the second control object's awareness of destroying and protecting oats, corresponding medium impact value evaluation methods are given for different judgment results to obtain medium impact values. Based on the average existence time, average number of existence, and occurrence frequency of the second control object, a high impact value is obtained. The primary impact value, medium impact value, and high impact value are combined to obtain the oat impact value of the control service object. Based on the oat impact value, the actual control object is screened from the second control object. Based on the individual information, behavioral information and existence information of the control service object, the impact of the control service object on oats is analyzed to decide whether to define it as a factor object that needs to be considered in the oat planting environment. This can reduce the ineffective waste of resources while fully considering the oat environment and improve the resource utilization rate of the planting environment control based on oat planting.

[0066] 3. Based on the oat impact values ​​of the actual control objects covered by the parameter application information, the corresponding object weight ratio is obtained. The parameter application information's impact on the parameter control objects is combined to determine the parameter demand of the parameter application information. The parameter application information's impact on the overall control objective is further comprehensively collected to determine the application demand of the parameter application information. The parameter application information's adjustment convenience is calculated by statistically analyzing the number of actual control objects covered by the parameter application information, the average adjustment range and average adjustment frequency of the actual control objects' response to the parameter application information, and the number of adjustment parameter devices referenced during the parameter application information adjustment process. Finally, the parameter demand and adjustment convenience are evaluated to determine the control reference of the parameter application information. The adjustment parameter device corresponding to the parameter application information with the highest control reference is selected as the primary reference device. The adjustment parameter device corresponding to the primary reference information is then controlled and adjusted based on real-time scene data, generating real-time adjustment data for the primary reference device as the primary reference data. Selecting the primary reference device based on the application demand and adjustment convenience of the parameter application information not only meets the requirements for oat cultivation environment adjustment but also significantly improves the adjustment convenience of the oat cultivation environment, enhancing the convenience of oat cultivation-based cultivation environment control. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 It is a schematic diagram of the specific steps of an embodiment of a planting environment control method based on oat planting of the present invention. DETAILED DESCRIPTION

[0068] Below is a combination of the embodiments and Figure 1 The present invention will be described in further detail, but the embodiments of the present invention are not limited thereto.

[0069] The present invention discloses a planting environment control method based on oat planting, which specifically comprises the following steps:

[0070] Step S1: collect real-time scene data of oat planting, and determine whether the oat planting environment has changed based on the real-time scene data.

[0071] Real-time scene data is extracted by monitoring equipment of the oat planting environment. The real-time scene data includes but is not limited to data such as temperature, humidity, and images of the oat planting area. By comparing the real-time scene data with the previous monitoring data, it is determined whether the degree of change reaches a threshold, thereby determining whether the oat planting environment has changed. For example, if 20 pests appear in the real-time scene data and 5 pests appear in the previous monitoring data, and the change threshold is 10 pests, then it is determined that the real-time scene data has changed. The change threshold can be implemented by the user's specific corresponding data, or it can be implemented by comparing the real-time scene data with the previous monitoring scene by similarity.

[0072] Step S2: If the oat planting environment changes, the control service object of the adjustment parameter device for controlling the planting environment is confirmed based on the real-time scene data.

[0073] Step S3: collecting object information of the control service object, and filtering the control service objects to obtain the actual control object according to the object information.

[0074] Step S4: Count all the adjustment parameter devices corresponding to the actual controlled objects and collect parameter application information of the adjustment parameter devices.

[0075] Different controlled objects have different environmental requirements, so their corresponding control parameter devices differ. For example, if workers are the controlled objects, then the control parameters for temperature, humidity, and air quality in an oat greenhouse are the control parameters for workers. Obviously, control parameters for fertilizers and pesticides don't address the environmental needs of workers, so they aren't considered control parameters for workers.

[0076] Step S5: selecting main reference information according to the parameter application information, and controlling the adjustment parameter device corresponding to the main reference information according to the real-time scene data to obtain main reference data.

[0077] Step S6: Control and adjust other adjustment parameter devices according to the main reference data and real-time scene data.

[0078] In practical applications, when controlling and regulating the oat cultivation environment, coordinated device control requires dynamic reference to monitoring data from other devices based on specific scenarios to achieve precise control. Different environmental factors (such as temperature, moisture, light, and soil) influence each other, and the regulation of a single device must rely on real-time data from related devices to avoid decision bias. For example, rising temperature evaporates moisture from the air, affecting humidity. However, adding water also lowers the temperature, creating a mutual influence. For example, if temperature is the primary reference information and the corresponding temperature control device is the primary adjustment parameter, the default temperature remains unchanged, while the humidity is automatically adjusted to meet environmental requirements. For example, if the current desired temperature is 25°C, the temperature remains unchanged, and the humidity is calculated based on the evaporation caused by the current temperature to generate the humidity adjustment data. However, if the humidity control device is the primary adjustment parameter, the humidity remains unchanged, and the temperature control device calculates the temperature drop caused by the current humidity and automatically adjusts the temperature to increase the data. The decision on which adjustment parameter device to use as the primary reference device in oat cultivation environmental regulation depends on the actual target of the cultivation environment. Setting the primary reference device based on actual conditions can improve the accuracy and convenience of oat cultivation environmental control and regulation.

[0079] If the oat planting environment changes, the steps for determining the control service object of the adjustment parameter device for the planting environment control based on the real-time scene data are as follows:

[0080] Step S21: obtaining a real-time control scheme for the oat planting environment, and extracting a control object corresponding to the real-time control scheme as an original control object.

[0081] While the oat growing environment primarily serves oats, other factors also need to be considered for optimal growth. For example, since oat cultivation depends on the soil, environmental regulation must also fully consider the soil to ensure that it meets the requirements of oat cultivation. Oat growth is highly dependent on soil microbiota, particularly arbuscular mycorrhizal fungi. Therefore, environmental regulation and control of oat cultivation also need to serve these microbial communities and reduce environmental impacts on their mortality.

[0082] Step S22 : extracting changed data according to the real-time scene data, and extracting a newly added control object as a changed control object according to the changed data and the original control object.

[0083] When the real-time scene changes, it is necessary to determine whether new control objects have been added. For example, if the humidity changes, the real-time scene can be compared with the last monitored scene to check whether new individuals have been added. If a person, cat, insect, or other new object appears in the scene, these are new control objects. Oats, soil, etc. are original control objects.

[0084] Step S23: forming a control service object based on the changed control object and the original control object.

[0085] In practice, when an individual appears in the oat-growing environment that was not previously present, the newly emerged individual is identified as a newly added control object and treated as a change control object. Because the scope of environmental control and regulation for oat cultivation is the oat-growing area, all individuals that appear within the regulated area are affected by the environmental regulation. Environmental regulation may need to consider these individuals, so these individuals are treated as control service objects to facilitate further screening. If there are no change control objects, the original control object is the actual control object, and the oat-growing environment is controlled and regulated according to the current control scheme, without the need to select a new primary reference device.

[0086] The steps of collecting object information of the control service object and filtering the actual control object from the control service object according to the object information are as follows:

[0087] Step S31: collecting the overall control target of the oat planting environment control and determining whether the control service object is associated with the overall control target.

[0088] Environmental control for oat cultivation has an overall goal—the ultimate objective. For example, some oats are cultivated for yield, others for quality, and still others to improve their environmental tolerance. Different overall control objectives determine the relationships between different control service objects and these objects. For example, animals like cats and dogs, which are control service objects, do not feed on oats and may trample on them, killing them and thus affecting yield. However, these creatures do not affect the quality of the oats. In other words, the height and nutritional value of the oats make them irrelevant to the overall control objective.

[0089] Step S32: Screen and remove control service objects that are not related to the overall control target to obtain a first control object.

[0090] Step S33 , determining whether the first controlled object is affected by the control of the parameter adjustment device, screening out the first controlled object that is not affected by the control of the parameter adjustment device, and obtaining the second controlled object.

[0091] Step S34: obtaining individual information of the second control object, and evaluating the primary impact value of the second control object on oats based on the individual information.

[0092] Step S35: Obtain behavior information of the second controlled object, and evaluate the medium impact value of the second controlled object according to the behavior information.

[0093] Step S36: Acquire the existence information of the second controlled object, and evaluate the high-level impact value of the second controlled object on oats according to the existence information.

[0094] Step S37, synthesizing the primary impact value, the medium impact value and the high impact value to obtain the oat impact value of the control service object, and screening the actual control object from the second control objects according to the oat impact value.

[0095] In practice, the primary and secondary impact values ​​are added together to form a base impact value, which is then multiplied by the corresponding higher impact value to obtain the oat impact value. If there are no primary and secondary impact values, meaning the second control object has no primary or secondary impact on oats, the oat impact value is simply 0. Because the object itself and its behavior do not affect oat growth, its presence or absence will have no effect on oats. Therefore, the higher impact value is evaluated based on the presence of primary and secondary impact values.

[0096] The step of determining whether the first controlled object is affected by the control of the parameter adjustment device is specifically:

[0097] Step S331 : determining whether the first control object senses the control adjustment of the adjustment parameter device; if so, collecting the application adjustment range of the adjustment parameter device.

[0098] Some service control objects are unaware of the adjustments made by the control parameter devices, meaning they are unaffected by the environment. For example, in an oat cultivation environment, tools such as hoes and shovels appear. These tools are indeed relevant to the overall oat control goal, but environmental adjustments do not affect their use. Therefore, although these are newly added entities, they do not need to be considered in environmental adjustments and are therefore unaffected by the control parameter devices.

[0099] Step S332: determining, based on the application adjustment range, whether the behavior characteristics of the first control object within the application adjustment range are affected.

[0100] Some individual objects are affected by the environment, but to ensure healthy oat growth, oat cultivation environments must be regulated within a certain range, not an infinite range. The optimum temperature range for oats during their growth period is 15-25°C, with an optimal temperature around 20°C. Temperatures ≥ 25°C hinder photosynthesis, while temperatures ≥ 38°C for four to five hours can cause stomatal atrophy, impacting pollination and grain filling. Therefore, the temperature regulation range for oats is 15-25°C, and this range cannot be exceeded. Therefore, even if environmental control adjustments require consideration of individual objects, they must not exceed the regulation range of oats; the primary goal is to protect oat growth. If individual objects are not affected within the applicable regulation range, the first control object is determined to be unaffected by the parameter-adjusting device. For example, if the operation of some smart devices or the work of workers during oat cultivation is indeed subject to environmental interference, but they are not affected within the environmental regulation range, these individuals do not need to be considered in environmental control.

[0101] Step S333: If the behavior characteristics of the first controlled object are not affected, it is determined that the first controlled object is not affected by the control of the parameter adjustment device.

[0102] Step S334: If the behavior characteristics of the first controlled object are affected, it is determined whether the change in the behavior characteristics of the first controlled object affects the overall control target.

[0103] Step S335: If the overall control target is affected, it is determined that the first controlled object is affected by the control of the adjustment parameter device.

[0104] In actual application, if the behavioral characteristics of the first control object are affected, it is determined whether the change in behavioral characteristics affects the overall control target. For example, the activity of certain oat pests varies within the adjusted temperature range, and their behavioral characteristics will change, which will affect the quality target of the oats. In this case, it is considered to be affected by the control of the adjustment parameter device, because the object can be affected by environmental adjustment, thereby affecting the planting target of the oats. If the change in behavioral characteristics does not affect the overall control target, it is considered that affecting the individual through environmental adjustment is meaningless to the growth of oats. For example, the first control object is a smart device, which is affected by the environment during operation, and its noise will be affected and changed. However, the noise level of the device does not affect the yield target of oat growth, so it is considered that the smart device is not affected by the control of the adjustment parameter device.

[0105] The steps of obtaining individual information of the second control object and evaluating the primary impact value of the second control object on oats based on the individual information are specifically as follows:

[0106] Step S341 : acquiring individual information of a second control object, and extracting object demand resources and information on environmental changes caused by the object to the environment based on the individual information.

[0107] Individual information includes the resource requirements of the subject and the environmental changes caused by the subject. This environmental change refers to the impact of the subject on the environment in which the oats are grown. For example, the growth of weeds will reduce the nutrients in the soil.

[0108] Step S342: Obtain oat demand resources and oat planting environment, and obtain competing resources based on the resource intersection of the oat demand resources and the object demand resources.

[0109] Step S343: Calculate the resource overlap based on the contention resources and the oat demand resources.

[0110] The resource overlap was obtained by comparing the ratio of the amount of competing resources to the amount of resources required by oats.

[0111] Step S344: extracting the object resource absorption rate of the second control object to the contention resource according to the individual information.

[0112] Resource absorption rate refers to the proportion of substances absorbed by organisms or systems from the external environment. For example, the absorption rate of soil nutrients by plants = absorption amount / total effective amount in the soil. Resource absorption rate can be defined as the efficiency of obtaining and internalizing resources from the environment, that is, the amount of absorbed resources / total available resources.

[0113] Step S345 , collecting the oat resource absorption rate of the competing resource by oat, and calculating the absorption rate difference between the target resource absorption rate and the oat resource absorption rate.

[0114] Step S346 , comparing the obtained environmental change information with the environmental similarity of the oat planting environment, and combining the resource overlap and the absorption rate difference to obtain the primary impact value of the second control object on the oats.

[0115] In practical applications, environmental similarity can be calculated using a Gaussian similarity function. Using the existing weighted linear superposition model, environmental similarity, combined with resource overlap and absorption rate differences, is then used to calculate the primary impact value. A greater environmental similarity indicates a smaller impact of the second control object on the environment, resulting in a smaller primary impact value. A greater absorption rate difference indicates that the second control object is more competitive in resource competition, potentially stealing resources from the oats and causing malnutrition, resulting in a larger primary impact value. Furthermore, a greater degree of resource overlap indicates that the two control objects compete for more resources, thus increasing their impact on the oats. For example, if the second control object is a weed, weed A requires different nutrients than oats and only competes for light, thus significantly impacting the oats. However, weed B requires the same nutrients as oats and competes for multiple resources, including nutrients and light, significantly impacting oat growth, resulting in a larger primary impact value.

[0116] The steps of obtaining behavior information of the second controlled object and evaluating the medium impact value of the second controlled object based on the behavior information are specifically as follows:

[0117] Step S351: Determine whether the second control object has a destructive intention in its behavior towards oats based on the behavior information.

[0118] Some controlled subjects may have destructive behaviors towards oats. For example, some birds (such as sparrows and crows) may peck at oat kernels, causing direct yield losses. Foraging is a survival instinct for birds, and since oats are a staple in their diet, they clearly have destructive intentions.

[0119] Step S352: If there is a destructive intention, the average destructive value of the second control object on the oats is extracted based on the behavior information as the medium impact value.

[0120] If there is a destructive intention, it means that the object will cause damage to the oats if it enters the oat planting environment, so the average damage value of the object to the oats is taken as the medium impact value. The average damage value of the second control object can be obtained based on the historical average damage loss or through expert evaluation.

[0121] Step S353: If there is no destructive awareness, it is determined based on the behavior information whether the second control object has a protective awareness towards the oats.

[0122] Some individuals have no intention of destroying oats, but also have a sense of protection. For example, when staff enter the oat-growing area, they will not destroy the oats, but will protect them to ensure their healthy growth.

[0123] Step S354: If there is no protection awareness, the object behavior characteristics are extracted based on the behavior information.

[0124] Some control subjects have neither the awareness of destroying nor the awareness of protecting oats, such as some puppies, kittens and other creatures. These creatures do not feed on oats, but they will not deliberately protect oats. At this time, their impact on oats is judged based on their behavioral characteristics.

[0125] Step S355: Obtain standard behavior characteristics for treating oats, and compare the feature similarity between the standard behavior characteristics and the object behavior characteristics as the autonomous control capability value.

[0126] For example, cats and dogs in farmland are primarily driven by scent tracking, territorial inspection, or curiosity, rather than targeting crops. Their routes are determined by obstacle distribution, surface roughness, and prey tracks, rather than by intentional avoidance of crops. However, the standard behavioral characteristics required for oats are movement based on the distribution of oats and avoidance of oats. The feature similarity calculated using the Gaussian similarity function is used as the autonomous control capability value.

[0127] Step S356: If there is protection awareness, the autonomous control capability value is the maximum value.

[0128] If there is a protective consciousness, it is believed that the second control object will autonomously control itself not to destroy the oats.

[0129] Step S357: establishing a correlation curve diagram between the autonomous control capability value of the second control object and the oat impact consequence, and finding the oat impact consequence as the medium impact value according to the correlation curve diagram.

[0130] In practice, the greater the object's autonomous control ability value, the more it can control its oat-destroying behavior. Different objects have different autonomous control abilities, and when their autonomous control abilities are insufficient, the damage they inflict on the oats also varies. The object's behavioral characteristics are real-time, and a correlation curve is established between the autonomous control ability value of the second control object and the consequences of its oat-destroying behavior. For example, when a puppy is in an oat-destroying environment and its feature similarity is minimal, the oat-destroying consequence it causes is a 30% loss. Therefore, the correlation curve established based on the puppy's autonomous control ability value shows a maximum oat-destroying consequence of 30%. For a bird that doesn't eat oats, when its feature similarity is minimal, its oat-destroying consequence is a 1% loss. Therefore, the correlation curve for its oat-destroying consequence is a maximum of 1%. A correlation curve is constructed based on the actual damage caused by the object and its current autonomous control ability value.

[0131] The steps of obtaining the existence information of the second control object and evaluating the high-level impact value of the second control object on oats according to the existence information are specifically as follows:

[0132] Step S361: Acquire the existence information of the second control object, and determine whether the appearance of the second control object is a fixed phenomenon according to the existence information.

[0133] Some control targets are stationary in oat greenhouses, such as workers who work at fixed times each day, or weeds and pests that become stationary in the oat growing environment. Historical monitoring data is obtained and, based on the historical monitoring data and the behavior of the control target, it is determined whether this is a stationary phenomenon.

[0134] Step S362: If it is a fixed phenomenon, the average existence duration and the average existence quantity are extracted according to the existence information.

[0135] Step S363: The high-level impact value of the second control object on oats is obtained by combining the average existence duration and the average existence quantity.

[0136] The average existence duration and average existence number can be calculated within a set time period, such as the average existence duration and average existence number within a day or a week, and the higher impact value can be obtained based on the weighted linear superposition model analysis.

[0137] Step S364: If the appearance of the second control object is not a fixed phenomenon, the appearance frequency of the second control object is counted as a high-level influence value.

[0138] In practice, the entry of the second controlled object into the oat growing environment is sporadic. If this is not a sporadic occurrence, the impact on oats is assessed based on the duration and number of instances of the second controlled object in the growing environment. The actual impact on oats is analyzed based on the scale of the second controlled object. If the second controlled object's entry is sporadic, its duration and number of instances are irrelevant, and the frequency of occurrence is used as the higher impact value. The higher the frequency, the greater the impact on oats.

[0139] The steps of selecting main reference information according to parameter application information, controlling the adjustment parameter device corresponding to the main reference information according to real-time scene data, and obtaining the main reference data are as follows:

[0140] Step S51 : collecting service impact information of parameter application information, and obtaining application demand of the parameter application information based on evaluation of the service impact information.

[0141] Step S52 : collecting adjustment information of the parameter application information, and obtaining the adjustment convenience of the parameter application information according to the evaluation of the adjustment information.

[0142] Step S53: The control reference degree of the parameter application information is obtained by combining the parameter demand degree and the adjustment convenience evaluation.

[0143] Using a weighted linear superposition model, we combined parameter demand and adjustment ease to evaluate the control reference. The greater the parameter demand, the greater the control reference. Because the parameter demand is high, it should be used as the primary reference information. The greater the adjustment ease, the easier it is to adjust the parameter, making it more convenient to use as the primary reference information. Therefore, the corresponding adjustment ease increases.

[0144] Step S54: Select the adjustment parameter device corresponding to the parameter application information with the largest control reference degree as the main reference device, control the adjustment parameter device corresponding to the main reference information according to the real-time scene data, and obtain the real-time adjustment data of the main reference device as the main reference data.

[0145] In actual use, after the main reference device is selected, its corresponding adjustment data needs to be sent to other adjustment control devices for reference, so the device needs to be adjusted first. Select all the adjustment parameter devices that need to be controlled and adjusted, and use their corresponding parameters as adjustment control parameters. Remove the adjustment control parameters from the real-time scene information, and use the remaining parameters to form the real-time environment information. Because the adjustment control parameters need to be readjusted after the main reference device is adjusted, there is no reference basis at this time. The main reference device needs to consider the fixed parameters that will not be adjusted later and provide the best adjustment plan. After the main reference device is adjusted, its adjustment data is sent to other adjustment parameter devices, and other adjustment parameter devices make adjustments based on this data.

[0146] The steps of collecting service impact information of parameter application information and evaluating the application demand of the parameter application information based on the service impact information are specifically as follows:

[0147] Step S511 , obtaining the actual control object covered by the parameter application information as the parameter control object, and comparing the oat impact value of the parameter control object to obtain the object weight ratio of the parameter control object.

[0148] Step S512 : collecting the influence of the parameter application information on the parameter control object, and obtaining the parameter demand of the parameter application information in combination with the corresponding object weight ratio.

[0149] The parameter requirement is calculated by multiplying the degree of impact by the corresponding object weight ratio. Since oats are the most important environmental control target in oat cultivation, parameter adjustments corresponding to these targets must consider the impact of the control target on oats. Therefore, the object weight ratio of the parameter control target is calculated based on the oat impact value. For example, temperature affects fertilizer, soil, and bacterial colonies. The greater the parameter's impact on each of these objects, the higher the parameter requirement. Because each object has varying importance, the impact of all objects is not simply added together. Instead, a weighted ratio is formed based on the oat impact value. The impact can be determined through expert assessment or by creating a curve that plots parameter change against the change in the parameter control target. For example, a one-degree increase in temperature results in an average loss of 5% in soil nutrients.

[0150] Step S513 : collecting the influence of the parameter application information on the overall control target, and combining the parameter demand to obtain the application demand of the parameter application information.

[0151] In practical applications, after determining the parameter requirements, the most important factor in regulating and controlling the oat growing environment is the oats themselves. Meeting the ultimate goals and requirements of oat cultivation is crucial. Therefore, it's necessary to consider not only the parameter requirements of various control objects but also the impact of parameter application information on the overall control objective. This is done using a weighted linear superposition model to determine the application requirements. Parameter application information refers to the relevant information during the actual application of the parameter, including the actual control objects covered and the degree of impact on the parameter's control object.

[0152] The steps of collecting adjustment information of parameter application information and evaluating the adjustment convenience of the parameter application information based on the adjustment information are specifically as follows:

[0153] Step S521 : Count the number of actual controlled objects covered by the parameter application information and record it as the number of objects.

[0154] Step S522 , collecting statistics on the average adjustment range and average adjustment frequency of the parameter application information of the actual controlled object.

[0155] Step S523 : Count the number of adjustment parameter devices referenced in the parameter application information adjustment process and record it as the number of devices.

[0156] Step S524 , comprehensively obtain the adjustment convenience of the parameter application information by combining the number of objects, the average adjustment range, the average adjustment frequency, and the number of devices.

[0157] In practical applications, the ease of adjustment can be derived through a weighted linear superposition model. During the adjustment process of environmental parameters, the greater the number of actual supply objects covered, the more difficult the adjustment, and therefore the lower the ease of adjustment. Some parameters have a larger adjustment range, such as fertilizer, which allows for changes in fertilizer type and amount. Therefore, the ease of adjustment is higher because they can be adjusted over a larger range. Some parameters, because they are affected by the surrounding environment, have a higher average adjustment frequency. For example, when the external temperature of an oat greenhouse changes, the internal temperature is also affected, and the temperature varies at different times of the day. Therefore, the higher the adjustment frequency, the lower the ease of adjustment, because frequent adjustments are required. In addition to referring to the main reference equipment, some equipment also requires consideration of auxiliary equipment during the adjustment process. The greater the number of devices, the more difficult the adjustment, and therefore the lower the ease of adjustment.

[0158] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A planting environment control method based on oat planting, characterized in that: The following steps are involved: Collect real-time scene data of oat planting and determine whether the oat planting environment has changed based on the real-time scene data; If the oat planting environment changes, the control service object of the adjustment parameter equipment for the planting environment control is confirmed based on the real-time scene data; Collect object information of the control service object, and filter the actual control object from the control service objects according to the object information; Count all the adjustment parameter devices corresponding to the actual controlled objects and collect the parameter application information of the adjustment parameter devices; Selecting primary reference information according to parameter application information, controlling the adjustment parameter device corresponding to the primary reference information according to real-time scene data, and obtaining primary reference data; Control and adjust other adjustment parameter devices based on the main reference data and real-time scene data.

2. A planting environment control method based on oat planting according to claim 1, characterized in that, If the oat planting environment changes, the steps of confirming the control service object of the adjustment parameter device for the planting environment control according to the real-time scene data are specifically as follows: Obtain a real-time control plan for the oat planting environment, and extract the control object corresponding to the real-time control plan as the original control object; Extract the changed data according to the real-time scene data, and extract the newly added control object as the changed control object according to the changed data and the original control object; A control service object is formed based on the changed control object and the original control object.

3. A planting environment control method based on oat planting according to claim 1, characterized in that, The step of collecting object information of the control service object and filtering the actual control object from the control service object according to the object information is specifically as follows: Collect the overall control objectives of oat planting environment control and determine whether the control service object is related to the overall control objectives; Screening and removing control service objects that are not related to the overall control objective to obtain a first control object; Determine whether the first controlled object is affected by the control of the parameter adjustment device, filter out the first controlled object that is not affected by the control of the parameter adjustment device, and obtain the second controlled object; obtaining individual information of a second control subject, and evaluating a primary impact value of the second control subject on oats based on the individual information; obtaining behavioral information of a second controlled object, and evaluating a medium impact value of the second controlled object based on the behavioral information; obtaining existence information of a second control object, and evaluating a high-level impact value of the second control object on oats based on the existence information; The primary impact value, the medium impact value and the high impact value are integrated to obtain the oat impact value of the control service object, and the actual control object is obtained by screening from the second control objects according to the oat impact value.

4. A method for controlling the planting environment based on oat planting according to claim 3, characterized in that: The step of determining whether the first controlled object is affected by the control of the parameter adjustment device is specifically: determining whether the first controlled object senses the control adjustment of the adjustment parameter device, and if so, collecting the application adjustment range of the adjustment parameter device; determining, based on the application adjustment range, whether a behavioral characteristic of the first control object within the application adjustment range is affected; If the behavioral characteristics of the first controlled object are not affected, it is determined that the first controlled object is not affected by the control of the parameter adjustment device; If the behavior characteristics of the first controlled object are affected, determining whether the change in the behavior characteristics of the first controlled object affects the overall control objective; If the overall control target is affected, it is determined that the first controlled object is affected by the control of the adjustment parameter device.

5. A method for controlling the planting environment based on oat planting according to claim 3, characterized in that: The step of obtaining individual information of the second control object and evaluating the primary impact value of the second control object on oats based on the individual information is specifically as follows: Acquire individual information of a second control object, and extract, based on the individual information, required resources of the object and information about environmental changes caused by the individual object to the environment; Obtain oat demand resources and oat planting environment, and obtain competitive resources based on the resource intersection of oat demand resources and object demand resources; The resource overlap was calculated based on the competing resources and oat demand resources; extracting the object resource absorption rate of the second control object for the competing resource according to the individual information; Collect the oat resource absorption rate of the competing resources and calculate the absorption rate difference between the target resource absorption rate and the oat resource absorption rate; The environmental change information and the environmental similarity of the oat planting environment are compared, and the primary impact value of the second control object on oats is obtained by combining the resource overlap and absorption rate difference.

6. A method for controlling the planting environment based on oat planting according to claim 3, characterized in that: The step of obtaining the behavior information of the second controlled object and evaluating the medium impact value of the second controlled object according to the behavior information is specifically as follows: Determine whether the second control subject has a destructive intention towards oats based on the behavioral information; If there is a sense of destruction, the average destruction value of the second control subject on oats is obtained based on the behavioral information extraction as the medium impact value; If there is no intention to destroy, then determine whether the second control subject has an intention to protect oats based on the behavior information; If there is no protection awareness, the behavior characteristics of the object are extracted based on the behavior information; Obtain standard behavioral characteristics for treating oats, and compare the characteristic similarity between the standard behavioral characteristics and the object behavioral characteristics as the autonomous control ability value; If there is protection awareness, the autonomous control ability value is the maximum value; A correlation curve diagram between the autonomous control capability value of the second control object and the oat impact consequence is established, and the oat impact consequence is obtained as the medium impact value according to the correlation curve diagram.

7. The method for controlling the planting environment based on oat planting according to claim 3, characterized in that: The step of obtaining the existence information of the second controlled object and evaluating the high-level impact value of the second controlled object on oats according to the existence information is specifically as follows: Acquiring existence information of a second control object, and determining whether the appearance of the second control object is a fixed phenomenon according to the existence information; If it is a fixed phenomenon, the average existence duration and average number of existence are extracted based on the existence information; The high impact value of the second control object on oats was obtained by combining the average existence duration and the average existence quantity; If the appearance of the second control object is not a fixed phenomenon, the appearance frequency of the second control object is counted as a high-level influence value.

8. The method for controlling the planting environment based on oat planting according to claim 3, characterized in that: The step of selecting main reference information according to parameter application information, and controlling the adjustment parameter device corresponding to the main reference information according to real-time scene data to obtain the main reference data is specifically as follows: Collecting service impact information of parameter application information, and obtaining application demand of the parameter application information based on the evaluation of the service impact information; Collecting adjustment information of the parameter application information, and obtaining adjustment convenience of the parameter application information based on the evaluation of the adjustment information; The control reference degree of parameter application information is obtained by combining the parameter demand degree and adjustment convenience evaluation; Select the adjustment parameter device corresponding to the parameter application information with the largest control reference degree as the main reference device, control the adjustment parameter device corresponding to the main reference information according to the real-time scene data, and obtain the real-time adjustment data of the main reference device as the main reference data.

9. A method for controlling the planting environment based on oat planting according to claim 8, characterized in that: The step of collecting the service impact information of the parameter application information and evaluating the application demand of the parameter application information based on the service impact information is specifically as follows: Obtain the actual control object covered by the parameter application information as the parameter control object, and compare the oat impact value of the parameter control object to obtain the object weight ratio of the parameter control object; The influence degree of the collected parameter application information on the parameter control object is combined with the corresponding object weight ratio to obtain the parameter demand degree of the parameter application information; The influence degree of the collected parameter application information on the overall control target is combined with the parameter demand degree to obtain the application demand degree of the parameter application information.

10. A method for controlling the planting environment based on oat planting according to claim 8, characterized in that: The step of collecting adjustment information of the parameter application information and evaluating the adjustment convenience of the parameter application information according to the adjustment information is specifically as follows: The number of actual control objects covered by the statistical parameter application information is recorded as the number of objects; Calculate the average adjustment range and average adjustment frequency of the actual controlled object's parameter application information; The number of adjustment parameter devices referenced in the parameter application information adjustment process is counted and recorded as the number of devices; The adjustment convenience of parameter application information is obtained by combining the number of objects, average adjustment range, average adjustment frequency and number of devices.

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