A method and system for intelligent adjustment of a shed environment

Abstract

A shed environment intelligent adjustment method and system belong to the field of intelligent control, the method comprises the following steps: collecting the age of meat ducks, determining the target breeding stage; collecting historical meat duck breeding records and analyzing to obtain the activity area demand of meat ducks in the target breeding stage, generating a first adjustment scheme; dynamically monitoring the target meat duck shed to obtain real-time environmental characteristics; obtaining environmental characteristic requirements to generate a second adjustment scheme; dynamically monitoring the breeding facilities in the target meat duck shed to obtain real-time facility characteristics to obtain a third adjustment scheme; and adjusting the environment of the target meat duck shed according to the obtained adjustment scheme. The application solves the technical problems of poor shed environment, high mortality rate of meat ducks, low breeding quality and efficiency in the prior art, realizes intelligent regulation and control of the environment of the meat duck shed, achieves intelligent optimization of the environment of the shed, reduces the mortality rate of meat ducks, and improves the breeding quality and efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent control, in particular to a shed environment intelligent adjustment method and system. BACKGROUND

[0002] With the improvement of people's living standards, the consumption of meat duck continues to increase, the meat duck breeding industry develops rapidly, the scale of meat duck breeding is continuously expanded, and the production capacity is continuously increased. Then, the traditional meat duck breeding shed is rough in regulating the growth environment of meat duck, lacks pertinence, and cannot adjust the environment in real time according to the growth demand of meat duck, so as to provide the most suitable growth environment for meat duck, resulting in poor growth environment of meat duck, high mortality, low breeding quality and efficiency of meat duck. SUMMARY

[0003] The present application provides a shed environment intelligent adjustment method and system, which aims to solve the technical problems of poor shed environment, high mortality of meat duck breeding, and low breeding quality and efficiency in the prior art.

[0004] In view of the above problems, the present application provides a shed environment intelligent adjustment method and system.

[0005] The first aspect of the present application provides a shed environment intelligent adjustment method, which comprises collecting the age of meat duck in the target meat duck shed, and determining the target breeding stage in combination with the preset meat duck stage scheme; collecting historical meat duck breeding records and analyzing to obtain the activity area demand of meat duck in the target breeding stage, and generating a first adjustment scheme for the meat duck cage in the target meat duck shed according to the activity area demand; dynamically monitoring the target meat duck shed through an environment monitoring component to obtain real-time environmental characteristics, wherein the real-time environmental characteristics include real-time temperature and humidity, real-time ventilation volume, and real-time bacteria and virus concentration; obtaining environmental characteristic demand, and generating a second adjustment scheme for real-time temperature and humidity, real-time ventilation volume and real-time bacteria and virus concentration according to the environmental characteristic demand; dynamically monitoring the breeding facilities in the target meat duck shed through a facility monitoring component to obtain real-time facility characteristics, wherein the real-time facility characteristics include real-time trough information, real-time water tank information and real-time manure information; analyzing the real-time trough information, real-time water tank information and real-time manure information to obtain a third adjustment scheme; and adjusting the environment of the target meat duck shed according to the first adjustment scheme, the second adjustment scheme and the third adjustment scheme.

[0006] In another aspect of the present application, a shed environment intelligent adjustment system is provided, which comprises: a target breeding stage module configured to collect the day-old of meat ducks in a target meat duck shed and determine a target breeding stage in combination with a preset meat duck stage scheme; a first adjustment scheme module configured to collect historical meat duck breeding records and analyze the activity area demand of the meat ducks in the target breeding stage to generate a first adjustment scheme for the meat duck cage in the target meat duck shed; a real-time environment feature module configured to dynamically monitor the target meat duck shed through an environment monitoring assembly to obtain real-time environment features, wherein the real-time environment features include real-time temperature and humidity, real-time ventilation volume, and real-time concentration of bacteria and viruses; a second adjustment scheme module configured to obtain environment feature requirements and generate a second adjustment scheme for the real-time temperature and humidity, real-time ventilation volume, and real-time concentration of bacteria and viruses; a real-time facility feature module configured to dynamically monitor the breeding facilities in the target meat duck shed through a facility monitoring assembly to obtain real-time facility features, wherein the real-time facility features include real-time trough information, real-time water tank information, and real-time manure information; a third adjustment scheme module configured to analyze the real-time trough information, real-time water tank information, and real-time manure information to obtain a third adjustment scheme; and an implementation environment adjustment module configured to adjust the environment of the target meat duck shed according to the first adjustment scheme, the second adjustment scheme, and the third adjustment scheme.

[0007] The one or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0008] Since the target breeding stage is determined by the day-old of the meat ducks in the target meat duck shed in combination with the preset meat duck stage scheme, the first adjustment scheme for the meat duck cage is generated according to the growth stage of the meat ducks and the historical breeding data to provide suitable activity space for the meat ducks, the target meat duck shed is dynamically monitored, the second adjustment scheme for the real-time temperature and humidity, real-time ventilation volume, and real-time concentration of bacteria and viruses is generated according to the environment feature requirements to adjust the temperature and humidity, ventilation volume, and concentration of bacteria and viruses in real time, the breeding facilities in the target meat duck shed are dynamically monitored, and the third adjustment scheme is obtained according to the trough, water tank, and manure information to intelligently control the feed, drinking water, and manure treatment, the target meat duck shed is intelligently adjusted according to the first, second, and third adjustment schemes, the technical problem of poor shed environment, high mortality rate of meat ducks, and low breeding quality and efficiency in the prior art is solved, the intelligent control of the shed environment of the meat ducks is achieved, the technical effect of intelligently optimizing the shed environment, reducing the mortality rate of the meat ducks, and improving the breeding quality and efficiency is achieved.

[0009] The above description is only a summary of the technical solutions of the present application, in order to more clearly understand the technical means of the present application, the specific embodiments of the present application can be implemented in accordance with the content of the description, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. Attached Figure Description

[0010] Figure 1 This application provides a possible flowchart of a method for intelligent adjustment of the shed environment;

[0011] Figure 2 This application provides a schematic flowchart illustrating a possible process for generating a first regulation scheme in an intelligent regulation method for shed environment.

[0012] Figure 3 This application provides a schematic flowchart illustrating a possible process for generating a third adjustment scheme in an intelligent adjustment method for shed environment.

[0013] Figure 4 This application provides a possible structural schematic diagram of an intelligent shed environment regulation system.

[0014] Explanation of reference numerals in the attached diagram: Target aquaculture stage module 11, First adjustment scheme module 12, Real-time environmental characteristics module 13, Second adjustment scheme module 14, Real-time facility characteristics module 15, Third adjustment scheme module 16, Implementation environment adjustment module 17. Detailed Implementation

[0015] The overall concept of the technical solution provided in this application is as follows:

[0016] This application provides a method and system for intelligently regulating the environment of a duck shed. Based on the growth stage of the ducks and historical breeding data, a first regulation scheme for the duck cages is generated to provide suitable activity space for the ducks. The shed environment is dynamically monitored, and a second regulation scheme is generated based on environmental characteristics and requirements, adjusting temperature, humidity, ventilation, and bacterial concentration in real time to optimize the growth environment. The shed facilities are also dynamically monitored, and a third regulation scheme is generated based on information from feed troughs, water troughs, and manure, intelligently controlling feed, water, and manure treatment to ensure environmental hygiene and the nutritional needs of the ducks.

[0017] The environment of the duck sheds is adjusted as a whole according to the first, second and third adjustment schemes to achieve refined management of the shed environment. Adjustment schemes are generated as needed to intelligently regulate the growth environment, thereby optimizing growth conditions, reducing the mortality rate of ducks, and improving breeding quality and efficiency.

[0018] After introducing the basic principles of this application, various non-limiting embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0019] Example 1

[0020] like Figure 1 As shown in the figure, this application provides a method for intelligent adjustment of the shed environment, the method comprising:

[0021] Step S100: Collect the age of the ducks in the target duck shed and determine the target breeding stage in combination with the preset duck breeding stage plan;

[0022] Specifically, the age of ducks in the target duck shed refers to the number of days the ducks have lived since birth. A pre-designed duck growth stage plan is a plan that divides the duck growth cycle into several stages based on the duck breed and specific breeding objectives, allowing for targeted breeding. Each growth stage corresponds to the duck's physiological characteristics, activity needs, and environmental conditions.

[0023] The age of the ducks in the duck shed is collected by the electronic tag reading device in the intelligent adjustment system. Combined with the preset duck growth stage plan, when the ducks reach the starting age of a certain growth stage, it is determined that the ducks have entered that growth stage, thus determining the target breeding stage of the ducks.

[0024] For example, the growth stages of meat ducks can be divided into the brooding period, the rearing period, the fattening period, and the final fattening period. During the brooding period, the ducks are 1-14 days old. At this stage, the ducks have just hatched and require higher temperatures (32-35°C) and denser stocking densities to maintain their body temperature. They have limited space to move around, and their main activities are feeding, drinking, and sleeping. Their feed intake is 5%-8% of their body weight. During the rearing period, the ducks are 15-28 days old. At this stage, their feathers and sensory organs develop rapidly, and the temperature can be appropriately lowered by about 2°C each day. They require more space to grow. Large activity space and environment promote activity, with feed intake at 8%-12% of duckling body weight; fattening period is 29-42 days old. During this stage, the ducks grow rapidly and are very active, requiring a larger activity area. The suitable environmental temperature range is 25-28°C, and feed intake is 12%-15% of duckling body weight; final fattening period is 43-49 days old. During this stage, the temperature is maintained at around 25°C, feed intake is 15% of duckling body weight, and increased activity promotes muscle growth to reach the selling weight.

[0025] By acquiring data on the age of ducks and determining their growth stages, we can lay the foundation for adjusting the subsequent growth environment, enabling refined management for different growth stages, implementing environmental optimization and control, and meeting the growth needs of ducks at different growth stages.

[0026] Step S200: Collect historical records of duck farming and analyze them to obtain the activity area requirements of the ducks in the target farming stage, and generate a first adjustment scheme for the duck cages in the target duck shed based on the activity area requirements;

[0027] Specifically, the historical breeding record refers to the record generated by the breeding activity of the target duck house in the past stage, including environmental data, growth data, disease data, etc., reflecting the growth condition and environmental suitability of the duck in different growth stages. The historical breeding record is obtained and uploaded to the database by the environmental monitoring equipment, electronic weighing system and breeding personnel input. The intelligent adjustment system extracts the historical breeding record of the target duck house from the database and analyzes it. The activity area demand is obtained by analyzing the historical breeding record. The activity area demand refers to the activity space required by the duck in a certain growth stage to meet the activity demand. Ducks in different breeding stages have different activity area demands. The first adjustment scheme refers to the duck cage size adjustment scheme generated according to the activity area demand, including expanding or reducing the length, width and height of the duck cage.

[0028] For example, the analysis result of the activity area demand in a certain stage is X square meters, and the current duck cage size is Y square meters. The intelligent adjustment system generates a cage adjustment scheme according to the difference between the activity area demand and the current duck cage size, which is the first adjustment scheme, such as expanding or reducing the length a meters, the width b meters and the height c meters, to adjust the duck cage size to X square meters.

[0029] By analyzing the historical breeding record to obtain the activity demand of the duck in the target breeding stage, and generating a duck cage size adjustment scheme accordingly, the duck cage space is adjusted to meet the activity demand of the duck, realizing the fine management of the environmental conditions, providing suitable activity space for ducks in different growth stages, and being beneficial to improve the quality of the duck.

[0030] Step S300: dynamically monitoring the target duck house by the environmental monitoring component to obtain real-time environmental characteristics, wherein the real-time environmental characteristics include real-time temperature and humidity, real-time ventilation volume, and real-time concentration of bacteria and viruses;

[0031] Specifically, the environmental monitoring component is used to monitor the environmental parameters of the target duck house in real time by various sensing devices to obtain environmental characteristic data. The environmental monitoring component includes a temperature and humidity sensor, a flow sensor and a pathogen concentration sensor. The temperature and humidity sensor uses an alcohol or mercury thermometer and a capacitive hygrometer to sense the temperature and relative humidity of the target duck house and convert the electrical signal into a digital signal output. The flow sensor uses a hot-wire flowmeter to detect the ventilation flow of the target duck house by measuring the change of the hot-wire resistance and outputs a digital flow signal. The pathogen concentration sensor uses immunosensor technology, designs antibodies for duck circovirus, avian influenza virus and other pathogens, detects the concentration of pathogens through the immune reaction between antibodies and pathogens, and converts the digital signal output.

[0032] According to the obtained real-time environmental characteristic data, the meat duck growth environment state data is obtained, whether the target meat duck shed environment is suitable for meat duck growth is judged, data support is provided for targeted environment regulation and production management, and real-time monitoring of the meat duck growth environment is realized.

[0033] Step S400: Obtain environmental characteristic requirements, and generate a second adjustment scheme of the real-time temperature and humidity, the real-time ventilation volume, and the real-time concentration of bacteria and viruses according to the environmental characteristic requirements;

[0034] Specifically, the environmental characteristic requirements refer to the suitable ranges of environmental factors such as temperature, humidity, ventilation volume, and pathogen concentration for meat ducks in different growth stages. The intelligent adjustment system pre-establishes an environmental characteristic requirement database according to the data such as the type, growth cycle, and breeding density of meat ducks, combined with environmental biology. The environmental characteristic requirements are obtained from the environmental characteristic requirement database to generate the second adjustment scheme, which provides a reference scheme for the regulation of real-time environmental characteristics, and determines the regulation targets and adjustable ranges of the temperature, humidity, ventilation volume, and pathogen concentration in the target meat duck shed.

[0035] For example, the second adjustment scheme generated by the intelligent adjustment system according to the environmental characteristic requirements of a certain target meat duck shed is: the suitable temperature range is 18-28°C, the regulation target temperature is 23°C; the relative humidity range is 60%-80%, the regulation target humidity is 70%; the ventilation volume range is 800-1200m3 / h, the regulation target ventilation volume is 1000m3 / h; and the pathogen concentration does not exceed 104cfu / m3.

[0036] According to the environmental characteristic requirements, the second adjustment scheme with adjustment targets and adjustable ranges is generated for environmental characteristics such as temperature, humidity, ventilation volume, and pathogen concentration. When the real-time environmental data does not meet the range of the second adjustment scheme, the real-time adjustment of the environmental characteristics is performed, so that the environmental state is maintained within the suitable range, the best growth environment is provided for the meat ducks, and precise adjustment of the shed environmental characteristics is realized, which ensures that the environmental factors are always maintained within the suitable range and optimizes the shed environment.

[0037] Step S500: The breeding facilities in the target meat duck shed are dynamically monitored by the facility monitoring component to obtain real-time facility characteristics, wherein the real-time facility characteristics include real-time trough information, real-time water tank information, and real-time manure information.

[0038] Specifically, the facility monitoring component monitors the breeding facilities in the target meat duck house, such as feed troughs, water troughs, and manure treatment systems, in real time through various sensing devices to obtain facility operation data. The facility monitoring component includes a feed trough monitor, a water trough monitor, and a manure monitor. The feed trough monitor is installed in the feed trough, uses a material height sensor to measure the height of the feed in the feed trough, and converts the analog signal into a digital signal output. At the same time, a camera is installed in the feed trough to take pictures regularly, and image processing technology is used to determine the condition of the material in the feed trough. The water trough monitor is installed in the water trough and includes a water level sensor and a water quality sensor to measure the water level and water quality of the water trough and output digital signals of the water level and water quality. The manure monitor is installed in the manure collection channel and includes a liquid level sensor and a component sensor to monitor the manure liquid level and main components and output digital signals of the manure liquid level and components.

[0039] The facility monitoring component obtains real-time facility characteristics such as real-time feed trough information, real-time water trough information, and real-time manure information of the target meat duck house to determine whether the facilities are working normally and provide data support for intelligent adjustment of the house environment.

[0040] Step S600: Analyzing the real-time feed trough information, real-time water trough information, and real-time manure information to obtain a third adjustment scheme.

[0041] Specifically, the third adjustment scheme refers to obtaining the normal operation range of the facilities by analyzing the real-time feed trough information, real-time water trough information, and real-time manure information, and combining the feed trough control plan, water trough control plan, and manure treatment control plan set according to the breeding requirements. For example, the third adjustment scheme for a certain target meat duck house is that the feeding alarm reference value in the feed trough control plan is 30% of the feed trough material height, and the feeding amount is 1 / 3 of the original material; the water level alarm reference value in the water trough control plan is 8 / 10 of the water trough, and the water source flow adjustment range is 500-3000 L per hour; the liquid level alarm reference value in the manure treatment control plan is 9 / 10 of the manure channel, and the sewage pump working range is 50%-100%.

[0042] When the real-time feed trough information, real-time water trough information, and real-time manure information show that the facility characteristics are outside the range of the third adjustment scheme, the intelligent adjustment system will start the corresponding alarm or control mechanism. Moreover, the intelligent adjustment system will continuously optimize the third adjustment scheme according to the facility operation status to realize fine management and control of the facilities, ensure stable operation of the facilities, and provide a foundation for environmental control and production management to improve the breeding quality and efficiency of meat ducks.

[0043] Step S700: Adjusting the environment of the target meat duck house according to the first adjustment scheme, the second adjustment scheme, and the third adjustment scheme.

[0044] Specifically, according to the first adjustment scheme, the second adjustment scheme and the third adjustment scheme, the environmental factors and facilities of the target meat duck house are comprehensively adjusted by the environmental control component in the intelligent adjustment system.

[0045] The first adjustment scheme is a cage space adjustment scheme determined according to meat duck growth data, and the target meat duck can use a cage width and height range. The intelligent adjustment system selects the most suitable value within the allowed range and automatically adjusts the cage size to provide sufficient activity space for meat ducks.

[0046] The second adjustment scheme is a temperature, humidity, ventilation and pathogen concentration control scheme generated according to the environmental feature requirement database. When the real-time environmental monitoring result exceeds the second adjustment scheme range, the environmental control component will start the corresponding device to adjust the environmental factors to maintain them in the appropriate range. For example, a certain second adjustment scheme is: the appropriate temperature range is 18-28°C, the relative humidity range is 60%-80%, the ventilation range is 800-1200m3 / h, and the pathogen concentration does not exceed 104cfu / m3. If the real-time temperature is 31°C higher than the upper limit of the appropriate range, the intelligent adjustment system will control the opening of the dehumidification and cooling device to reduce the temperature of the duck house; if the real-time humidity is 55% lower than the lower limit of the appropriate range, the intelligent adjustment system will control the opening of the humidifier to increase the air humidity; if the real-time ventilation is too large, the intelligent adjustment system will reduce the ventilation speed or stop the machine to reduce the ventilation; if the real-time pathogen concentration reaches 106cfu / m3, the intelligent adjustment system will open the air disinfection device to disinfect the air and reduce the concentration to the appropriate range.

[0047] The third adjustment scheme is a feed trough control plan, a water trough control plan and a manure treatment control plan set according to real-time facility features. When the real-time facility monitoring result exceeds the third adjustment scheme range, the intelligent adjustment system will start the alarm or control mechanism to adjust the operation status of the feeding facility to ensure its normal work. For example, if the feed trough material height is too low, a feeding alarm will be issued; if the water trough water level is too high, the water source will be turned off to prevent overflow; if the manure liquid level is too high, the manure pump speed will be increased to increase the sewage amount.

[0048] According to the first adjustment scheme, the second adjustment scheme and the third adjustment scheme, the cage space, the temperature, humidity, ventilation and pathogen concentration are intelligently adjusted to control the feeding facility. All environmental factors and facilities in the target meat duck house are monitored, managed and controlled to optimize the house environment, realize the intelligent control of the growth environment in all directions, and achieve the purpose of improving the breeding efficiency and breeding quality.

[0049] Further, the embodiments of the present application also include:

[0050] Step S810: monitoring the real-time blood oxygen level of the meat duck;

[0051] Step S820: judging whether the real-time blood oxygen level belongs to a predetermined blood oxygen threshold value;

[0052] Step S830: if not, calling a predetermined regulation scheme to perform environmental regulation on the target duck house.

[0053] Specifically, the real-time blood oxygen level of the target duck is monitored by a blood oxygen monitoring device, which includes a blood oxygen sensor, a data acquisition module, and a data transmission module. The blood oxygen sensor can monitor the oxygen saturation in the blood of the duck using a photoelectric oximeter. The data acquisition module acquires the signal of the blood oxygen sensor and converts it into a digital signal. The data transmission module transmits the digital signal to the intelligent regulation system.

[0054] According to the physiological characteristics of the duck and the environmental conditions, a normal blood oxygen level range is set in advance, which is generally set to 85%-95%, as the predetermined blood oxygen threshold value. The intelligent regulation system judges the obtained real-time blood oxygen data to determine whether it is within the normal range. When the real-time blood oxygen data does not belong to the predetermined blood oxygen threshold value, i.e., it is outside the normal range, the intelligent regulation system will call the corresponding predetermined regulation scheme to adjust the environmental factors or facilities of the target duck house to restore the blood oxygen level of the duck to a normal state. According to the preset regulation scheme, when the real-time blood oxygen is too high, the ventilation volume is increased, the dehumidification device is started to reduce the temperature, and the consumption of blood oxygen by the duck is accelerated; when the real-time blood oxygen is too low, the ventilation volume is reduced, the heater is turned on to increase the temperature, and the consumption of blood oxygen is slowed down.

[0055] The blood oxygen monitoring device monitors the blood oxygen status of the duck in real time to provide a reference for environmental regulation. When the blood oxygen data reflects abnormalities in the cage, the environment, or the facilities, the preset regulation scheme is started to correct it, ensuring that the blood oxygen level is always maintained within the normal physiological range, achieving precise regulation of the growth environment of the duck, and meeting the high-quality growth of the duck.

[0056] Further, the embodiments of the present application also include:

[0057] Step S831: extracting a first record in the historical duck breeding record, wherein the first record includes a first blood oxygen level, a first environmental feature, and a first facility feature of a first duck;

[0058] The first environmental feature includes a first temperature and humidity, a first ventilation volume, and a first concentration of bacteria and viruses.

[0059] The first facility feature includes first feeding trough information, first water tank information, and first fecal pollution information.

[0060] Step S832: taking the first temperature and humidity, the first ventilation volume, the first bacteria and virus concentration, the first trough information, the first water tank information, and the first fecal pollution information as independent variables, and taking the first blood oxygen level as a dependent variable;

[0061] Step S833: obtaining a correlation analysis result of the independent variables and the dependent variable, and formulating the predetermined regulation scheme according to the correlation analysis result.

[0062] Specifically, the blood oxygen level data of meat ducks and the environmental characteristic data and facility characteristic data in the shed are extracted from the historical breeding database, which are the first record of the historical meat duck breeding record. The environmental characteristic data includes temperature and humidity, ventilation volume, and pathogen concentration; the facility characteristic data includes trough information, water tank information, and fecal pollution information. The first record contains the full range of growth environment data of meat ducks at different growth stages, which provides a reference for the predetermination of the regulation scheme.

[0063] The environmental characteristic data and facility characteristic data are extracted, the first temperature and humidity, the first ventilation volume, the first bacteria and virus concentration, the first trough information, the first water tank information, and the first fecal pollution information are taken as independent variables, and the blood oxygen level data of meat ducks at the corresponding growth stage are taken as a dependent variable, and correlation analysis is performed. The correlation analysis method can be Pearson correlation analysis, Spearman rank correlation analysis, Kendall rank correlation analysis, discriminant analysis, etc. For example, the Pearson correlation coefficient between temperature and blood oxygen in a target shed environment is 0.8 through Pearson correlation analysis, which shows a strong positive correlation, i.e. the temperature rises, which leads to the rise of blood oxygen. According to the correlation analysis result, it can be judged which environmental factors or facility characteristics are related to the change of blood oxygen, which provides a basis for the targeted predetermination of the regulation scheme.

[0064] At the same time, a meat duck breeding expert group is established to analyze and determine the blood oxygen influencing factors and verify the correlation analysis result. If the environmental factors with strong correlation are consistent with the existing theory or model, it can preliminarily support the influence on blood oxygen. If the correlation result is inconsistent with the existing knowledge, it needs to be further verified by collecting other data or considering whether it is caused by accidental error. The verified correlation result can be used as the basis for formulating the regulation scheme. The influencing factors include meat duck feed intake, shed humidity, feed energy, etc. Finally, the predetermined regulation scheme is formulated in combination with the subjective analysis of the expert group and the objective analysis of the historical data. For example, the analysis result shows that the temperature and blood oxygen present a significant positive correlation, and the regulation scheme can include: when the blood oxygen is too high, start the dehumidification and cooling device; when the blood oxygen is too low, turn off the dehumidification and cooling device.

[0065] The blood oxygen influencing factor is determined by the subjective and objective combination, the corresponding relationship between the environmental characteristics and the blood oxygen change is more complete and effective, the real-time blood oxygen level is beneficial to accurate regulation and control of the environmental data, and the growth environment of the meat ducks is optimized.

[0066] Further, as shown in Figure 2 The embodiment of the application further includes:

[0067] Step S210: extracting a second record in the historical meat duck breeding record, wherein the second record refers to a breeding record of a second meat duck;

[0068] The second record includes a second body width time sequence, a second body height time sequence and a second active index time sequence of the second meat duck in the target breeding stage.

[0069] Step S220: comparing and analyzing the second body width time sequence and the second active index time sequence to obtain a meat duck cage width;

[0070] Step S230: comparing and analyzing the second body height time sequence and the second active index time sequence to obtain a meat duck cage height;

[0071] Step S240: taking the meat duck cage width and the meat duck cage height as an adjustment reference to generate the first adjustment scheme.

[0072] Specifically, the intelligent adjustment system extracts the body width, the body height and the active index of the meat duck at different times in the target breeding stage from the target meat duck shed historical breeding record database as the second record. The body width time sequence and the body height time sequence represent the change of the body size of the meat duck with time, and the active index time sequence represents the change of the activity frequency and the activity amplitude of the meat duck with time, wherein the activity amplitude includes the up-down activity amplitude and the left-right activity amplitude. The corresponding activity frequency and amplitude of the meat duck are different with the change of the body width and the body height in different growth stages.

[0073] Through the second body width timing, the time points when the body width of the meat duck starts to increase, is basically stable and starts to decrease are recorded, which are T1, T2 and T3 respectively. In the meat duck molting period or in the case of environmental emergency, the body width of the meat duck may decrease. Through the second active index timing, the time points when the active index starts to rise, reaches the peak and starts to decline are recorded, which are T1', T2' and T3' respectively. T1 and T1', T2 and T2', and T3 and T3' are compared. According to the comparison result, the meat duck cage width meeting the activity area requirement is obtained. If T2 and T2' are closest, it is judged that the current cage width basically meets the activity requirement of the meat duck at the T2 time point, and the cage width at this time point is recorded as the meat duck cage width. If T1 and T1' are closest, it indicates that the cage width is small and cannot meet the activity requirement of the meat duck. If T3 and T3' are closest, it indicates that the cage width is large and provides excess space.

[0074] Similar to the meat duck cage width judgment, the intelligent adjustment system compares and analyzes the second body height timing and the second active index timing, records the cage height corresponding to the time point when the body height stable period and the active peak time are closest, and obtains the meat duck cage height meeting the activity area requirement.

[0075] The intelligent adjustment system takes the meat duck cage width and the meat duck cage height judged as the basis for cage space adjustment, generates a first adjustment scheme for the current cage size, generates a cage space reduction scheme if all the current cage space sizes are greater than the judgment result, generates a cage space expansion scheme if all the current cage sizes are smaller than the judgment result, and adjusts only the item if only one item is greater than or smaller than the judgment result.

[0076] By extracting the meat duck growth record, analyzing the body size and activity change, and judging the appropriate cage space of the target breeding stage, a first adjustment scheme is generated, which can finely optimize the growth environment of the meat duck and improve the breeding quality of the meat duck.

[0077] Further, as shown in Figure 3 the embodiment of the present application further comprises:

[0078] Step S610: the real-time trough information includes real-time feed quality;

[0079] A predetermined feed threshold is obtained, and a feed adjustment scheme is obtained in combination with the real-time feed quality;

[0080] Step S620: the real-time water tank information includes real-time drinking water quality;

[0081] A predetermined drinking water threshold is obtained, and a drinking water adjustment scheme is obtained in combination with the real-time drinking water quality;

[0082] Step S630: the real-time fecal information includes real-time fecal quality;

[0083] a predetermined manure threshold is obtained, and a manure adjustment scheme is obtained in combination with the real-time manure quality;

[0084] Step S640: the feed adjustment scheme, the drinking water adjustment scheme, and the manure adjustment scheme jointly constitute the third adjustment scheme.

[0085] Specifically, the real-time feedlot information includes real-time feed quality, measured in kg. The intelligent adjustment system pre-sets a normal feed quality variation range as a predetermined feed threshold according to the type of meat ducks and growth requirements. The real-time feed quality is compared with the feed threshold. If the real-time feed quality exceeds the feed threshold range, the feed supply strategy is adjusted accordingly, which is the feed adjustment scheme. For example, the intelligent adjustment system pre-sets 5% to 10% daily increase in feed quality as the feed threshold range. On a certain day, the real-time feed quality increases by 12%, exceeding the predetermined threshold range. At this time, the feed adjustment scheme is to reduce the next day's feed input by 3% to control the feed quality.

[0086] The real-time feedlot information includes real-time drinking water volume, measured in liters. A normal drinking water volume variation range is pre-set as a drinking water threshold. The real-time drinking water volume is compared with the drinking water threshold. If it exceeds the range, the drinking water supply is adjusted, and the drinking water adjustment scheme is formulated. For example, 3% to 8% daily increase in drinking water volume is pre-set as the drinking water threshold range. On a certain day, the real-time drinking water volume increases by 1%, which is lower than the predetermined threshold range. At this time, the drinking water adjustment scheme can be formulated to increase the drinking water supply time to increase the drinking water volume of the meat ducks.

[0087] The real-time manure information includes real-time manure quality, measured in kg. A normal manure quality variation range is pre-set as a manure threshold. The real-time manure quality is compared with the predetermined manure threshold. If it exceeds the range, the manure treatment is adjusted, and the manure adjustment scheme is formulated. For example, 5% to 12% daily increase in manure quality is pre-set as the manure threshold range. On a certain day, the real-time manure quality increases by 18%, exceeding the predetermined threshold range. At this time, the manure adjustment scheme can be formulated to increase the manure cleaning by 1 time to speed up the manure removal speed, control the manure volume, and optimize the shed environment.

[0088] The feed adjustment scheme, the drinking water adjustment scheme, and the manure adjustment scheme are integrated to form the third adjustment scheme. From the aspects of meat duck feed supply, drinking water supply, and manure treatment, the physiological needs of the meat ducks are guaranteed, the shed environment is regulated, dynamic monitoring and precise control of the shed environment are achieved, the quality of the meat duck growth environment is improved, and the quality and efficiency of meat duck breeding are improved.

[0089] Further, the embodiments of the present application also include:

[0090] The real-time trough information includes a real-time feed image;

[0091] Step S650: segmenting the real-time feed image to obtain a set of segmented image blocks, wherein the set of segmented image blocks includes M image blocks, and M is an integer greater than 1;

[0092] Step S660: extracting a first image block from the M image blocks and performing discrete cosine transform on the first image block to obtain a first discrete cosine coefficient;

[0093] The first discrete cosine coefficient includes a first direct current coefficient and a first alternating current coefficient.

[0094] Step S670: calculating a first eigenvalue of the first image block according to the first direct current coefficient and the first alternating current coefficient;

[0095] Step S680: summing the first eigenvalue to obtain an eigenvalue of the real-time feed image;

[0096] Step S690: determining whether the eigenvalue is within a predetermined eigenvalue threshold;

[0097] Step S6100: if not, issuing a cleaning instruction and calling a predetermined feed adjustment scheme according to the cleaning instruction;

[0098] Step S6200: adding the predetermined feed adjustment scheme to the third adjustment scheme.

[0099] Specifically, the real-time trough information includes a real-time feed image, which is segmented into M image blocks by using edge detection, threshold method, texture analysis and other technologies to segment out target image blocks different from the background. M is an integer greater than 1, representing the number of segmented image blocks.

[0100] The first image block in the M segmented image blocks is selected, a discrete cosine transform is performed on the first image block to convert the image block from a spatial domain to a frequency domain, and a first discrete cosine coefficient is obtained. The first discrete cosine coefficient includes a first direct current coefficient and a first alternating current coefficient. The first direct current coefficient is related to the average intensity and overall illumination of the first image block, and can be used to determine the freshness of the real-time feed. If the first direct current coefficient is large, it indicates that the overall brightness of the first image block and the real-time feed image is high, and the color is light, and the real-time feed is relatively fresh. If the first direct current coefficient is small, the color of the real-time feed image is deepened, and the freshness of the real-time feed may decrease, and there may be problems such as deterioration or abnormal feed ratio. The first alternating current coefficient is related to the texture and contour complexity of the first image block, and can be used to determine the quality of the real-time feed. If the first alternating current coefficient contains more high-frequency components, more detailed features such as block distribution and unclear edges appear in the image, indicating that the real-time feed may have a caking phenomenon.

[0101] The ratio of the first direct current coefficient and the first alternating current coefficient is calculated as a first frequency feature value, which is a quantitative index and ranges from -1 to 1, reflecting the relationship between the overall illumination and the detail complexity of the first image block. The feature values of the M image blocks are x1, x2, …, xm respectively. The feature values of the M image blocks are added to obtain the feature value of the real-time feed image, which reflects the overall characteristics of the real-time feed image and serves as a basis for determining the image state. The feature value of the real-time feed image is the sum of the feature values of each image block, so the predetermined feature value threshold range is between -M and M. The closer the feature value of the real-time feed image to M or -M, the larger the proportion of the uniform region or the heterogeneous region in the real-time feed image. If the feature value of the real-time feed image is close to 0, it indicates that the uniform region, the transition region and the heterogeneous region in the real-time feed image have a comparable proportion, and the feed state is relatively good.

[0102] When the feature value of the real-time feed image exceeds the predetermined feature value threshold range, it indicates that the state of the real-time feed has changed, a cleaning instruction is issued, and a predetermined feed adjustment scheme is called. The predetermined feed adjustment scheme includes increasing or decreasing the feed input amount, adjusting the next feeding time, etc. The predetermined feed adjustment scheme is added to the third adjustment scheme to intelligently adjust the shed facility.

[0103] By segmenting, discrete cosine transforming and calculating the feature value of the real-time feed image in the real-time trough information, the feature value reflecting the state of the real-time feed is obtained, and the feature value is determined whether it exceeds the predetermined threshold to adjust the feed, so as to accurately monitor the change of the feed state, improve the feeding quality of the meat ducks, and thus improve the breeding quality of the meat ducks.

[0104] Further, the embodiments of the present application also include:

[0105] Step S910: based on a preset period, the target meat duck house is inspected to obtain an inspection information list;

[0106] The inspection information list includes N dead meat ducks in N inspections, and N is greater than or equal to 0.

[0107] Step S920: analyzing the N dead meat ducks in the N inspections to obtain N death causes.

[0108] Step S930: based on the N death causes, the environment of the target meat duck house is adjusted.

[0109] Specifically, the preset period is determined according to the growth stage of meat ducks and the frequency of environmental changes, etc. For example, 3-4 times a day, with an interval of 8 hours. The target meat duck house includes breeding areas, feeding areas, and manure treatment areas. According to the inspection period, the target meat duck house is inspected to obtain an inspection information list, which includes N dead meat ducks found in N inspections and the positioning of the dead meat ducks. N is an integer greater than or equal to 0, representing the number of dead meat ducks.

[0110] The N dead meat ducks obtained in the N inspections are analyzed by means of autopsy and pathological section observation to determine the N death causes, including high temperature, small cage size, disease, etc., which provide a basis for subsequent environmental adjustment. Based on the determined N death causes, the environment of the target meat duck house is adjusted, including adjusting temperature and humidity, opening or closing ventilation, adjusting water supply frequency, and replacing feed ratio, etc. For example, if the death cause is related to high temperature, the temperature of the house is lowered and the ventilation amount is increased; if it is related to water source, the corresponding equipment needs to be checked and repaired; if it is related to fecal pollution, the fecal pollution needs to be cleaned up and the house needs to be disinfected.

[0111] By obtaining the death information of meat ducks through inspection, analyzing the death causes, and adjusting the environment of the house according to the analysis results, other meat ducks can be effectively prevented from having the same problem, the mortality rate of meat ducks can be reduced, and the quality and efficiency of meat duck breeding can be improved.

[0112] In summary, the intelligent adjustment method for the environment of the house provided by the embodiments of the present application has the following technical effects:

[0113] The day age of the meat ducks in the target meat duck shed is collected, and a target breeding stage is determined in combination with a preset meat duck stage scheme, serving as a basis for subsequent adjustment scheme making; historical meat duck breeding records are collected and analyzed to obtain activity area requirements of the meat ducks in the target breeding stage, and a first adjustment scheme of the meat duck cage in the target meat duck shed is generated according to the activity area requirements; and the suitable activity area of the meat ducks is determined according to the growth characteristics of the meat ducks. The target meat duck shed is dynamically monitored by the environment monitoring component to obtain real-time environmental characteristics, wherein the real-time environmental characteristics include real-time temperature and humidity, real-time ventilation volume, and real-time bacterial and viral concentration, and the key environmental parameters are monitored in real time to provide data support for subsequent environmental adjustment; the environmental characteristic requirements are obtained, and a second adjustment scheme of the real-time temperature and humidity, the real-time ventilation volume, and the real-time bacterial and viral concentration is generated according to the environmental characteristic requirements, thereby providing a scheme basis for optimizing the growth environment; the breeding facilities in the target meat duck shed are dynamically monitored by the facility monitoring component to obtain real-time facility characteristics, wherein the real-time facility characteristics include real-time trough information, real-time water tank information, and real-time manure information, thereby providing data support for subsequent facility adjustment; the third adjustment scheme is obtained by analyzing the real-time trough information, the real-time water tank information, and the real-time manure information; the target meat duck shed is adjusted according to the first adjustment scheme, the second adjustment scheme, and the third adjustment scheme, the overall optimization of the growth environment is realized according to the obtained scheme, the intelligent regulation and control of the meat duck shed environment is realized, the intelligent optimization of the shed environment is achieved, the mortality rate of the meat ducks is reduced, and the breeding quality and efficiency are improved.

[0114] Embodiment Two

[0115] Based on the same inventive concept as the intelligent adjustment method of the shed environment in the foregoing embodiments, as shown in Figure 4 the embodiment of the present application provides a shed environment intelligent adjustment system, which comprises:

[0116] A target breeding stage module 11 is configured to collect the day age of the meat ducks in the target meat duck shed and determine the target breeding stage in combination with a preset meat duck stage scheme.

[0117] A first adjustment scheme module 12 is configured to collect historical meat duck breeding records and analyze the activity area requirements of the meat ducks in the target breeding stage, and generate a first adjustment scheme of the meat duck cage in the target meat duck shed according to the activity area requirements.

[0118] A real-time environmental characteristic module 13 is configured to dynamically monitor the target meat duck shed by the environment monitoring component to obtain real-time environmental characteristics, wherein the real-time environmental characteristics include real-time temperature and humidity, real-time ventilation volume, and real-time bacterial and viral concentration.

[0119] a second adjustment scheme module 14 configured to obtain environmental characteristic requirements and generate a second adjustment scheme of the real-time temperature and humidity, the real-time ventilation volume, and the real-time concentration of bacteria and viruses according to the environmental characteristic requirements;

[0120] a real-time facility characteristic module 15 configured to dynamically monitor breeding facilities in the target meat duck house through a facility monitoring assembly to obtain real-time facility characteristics, wherein the real-time facility characteristics include real-time trough information, real-time water tank information, and real-time manure information;

[0121] a third adjustment scheme module 16 configured to analyze the real-time trough information, the real-time water tank information, and the real-time manure information to obtain a third adjustment scheme;

[0122] an environmental adjustment module 17 configured to adjust the environment of the target meat duck house according to the first adjustment scheme, the second adjustment scheme, and the third adjustment scheme.

[0123] Further, the embodiments of the present application also include:

[0124] a real-time blood oxygen level module configured to monitor a real-time blood oxygen level of the meat duck;

[0125] a blood oxygen level judgment module configured to judge whether the real-time blood oxygen level belongs to a predetermined blood oxygen threshold;

[0126] a predetermined control scheme module configured to call a predetermined control scheme to adjust the environment of the target meat duck house if the real-time blood oxygen level does not belong to the predetermined blood oxygen threshold.

[0127] Further, the embodiments of the present application also include:

[0128] a first record module configured to extract a first record in the historical meat duck breeding record, wherein the first record includes a first blood oxygen level, first environmental characteristics, and first facility characteristics of a first meat duck;

[0129] wherein the first environmental characteristics include first temperature and humidity, a first ventilation volume, and a first concentration of bacteria and viruses;

[0130] wherein the first facility characteristics include first trough information, first water tank information, and first manure information;

[0131] a dependent variable module configured to take the first temperature and humidity, the first ventilation volume, the first concentration of bacteria and viruses, the first trough information, the first water tank information, and the first manure information as independent variables and take the first blood oxygen level as a dependent variable;

[0132] The control scheme formulation module is configured to obtain a correlation analysis result of the independent variable and the dependent variable, and formulate the predetermined control scheme according to the correlation analysis result.

[0133] Further, the embodiment of the present application further comprises:

[0134] The second recording module is configured to extract a second record in the historical meat duck breeding record, wherein the second record refers to a breeding record of a second meat duck.

[0135] The second record comprises a second body width time sequence, a second body height time sequence and a second active index time sequence of the second meat duck in the target breeding stage.

[0136] The meat duck cage width module is configured to compare and analyze the second body width time sequence and the second active index time sequence to obtain a meat duck cage width.

[0137] The meat duck cage height module is configured to compare and analyze the second body height time sequence and the second active index time sequence to obtain a meat duck cage height.

[0138] The first adjustment scheme module is configured to take the meat duck cage width and the meat duck cage height as adjustment criteria to generate the first adjustment scheme.

[0139] Further, the embodiment of the present application further comprises:

[0140] The real-time trough information comprises real-time feed quality.

[0141] The feed adjustment scheme module is configured to obtain a predetermined feed threshold value, and combine the real-time feed quality to obtain a feed adjustment scheme.

[0142] The real-time water tank information comprises real-time drinking water quality.

[0143] The drinking water adjustment scheme module is configured to obtain a predetermined drinking water threshold value, and combine the real-time drinking water quality to obtain a drinking water adjustment scheme.

[0144] The real-time fecal information comprises real-time fecal quality.

[0145] The fecal adjustment scheme module is configured to obtain a predetermined fecal threshold value, and combine the real-time fecal quality to obtain a fecal adjustment scheme.

[0146] The third adjustment scheme module is configured to combine the feed adjustment scheme, the drinking water adjustment scheme and the fecal adjustment scheme to obtain the third adjustment scheme.

[0147] Further, the embodiment of the present application further comprises:

[0148] The real-time trough information comprises a real-time feed image.

[0149] an image segmentation module configured to segment the real-time feed image to obtain a set of segmented image blocks, wherein the set of segmented image blocks comprises M image blocks, M being an integer greater than 1;

[0150] a first discrete cosine coefficient module configured to extract a first image block from the M image blocks and perform discrete cosine transform on the first image block to obtain a first discrete cosine coefficient;

[0151] wherein the first discrete cosine coefficient comprises a first direct current coefficient and a first alternating current coefficient;

[0152] a first eigenvalue module configured to calculate a first eigenvalue of the first image block according to the first direct current coefficient and the first alternating current coefficient;

[0153] an eigenvalue adding module configured to add the first eigenvalue to obtain an eigenvalue of the real-time feed image;

[0154] an eigenvalue judging module configured to judge whether the eigenvalue is within a predetermined eigenvalue threshold;

[0155] an adjustment scheme calling module configured to issue a cleaning instruction and call a predetermined feed adjustment scheme according to the cleaning instruction if the eigenvalue is not within the predetermined eigenvalue threshold;

[0156] an adjustment scheme adding module configured to add the predetermined feed adjustment scheme to the third adjustment scheme.

[0157] Further, the embodiments of the present application further comprise:

[0158] a patrol information list module configured to patrol the target meat duck house based on a preset period to obtain a patrol information list;

[0159] wherein the patrol information list comprises N dead meat ducks from N patrols, N being greater than or equal to 0;

[0160] a death cause obtaining module configured to analyze the N dead meat ducks from the N patrols to obtain N death causes;

[0161] an environment adjustment module configured to adjust the environment of the target meat duck house based on the N death causes.

[0162] Any step of the above method can be stored as computer instructions or programs in an unlimited computer memory and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, and no redundant limitation is made herein.

[0163] Further, the first or second possible not only represents the order relationship, but also can represent a specific concept, and / or refers to the single or all selection between multiple elements. Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the scope of the application. Thus, if these modifications and variations of the present application fall within the scope of the present application and equivalent technology, then the present application is intended to include these modifications and variations.

Claims

1. A method for intelligent adjustment of a shed environment, characterized in that The method comprises the following steps: Collecting the age of meat ducks in the target meat duck house, and determining the target breeding stage according to a preset meat duck stage scheme; Collecting historical meat duck breeding records and analyzing the activity area demand of the meat ducks in the target breeding stage, and generating a first adjustment scheme for the meat duck cages in the target meat duck house according to the activity area demand; Performing dynamic monitoring on the target meat duck house through an environmental monitoring component to obtain real-time environmental characteristics, wherein the real-time environmental characteristics include real-time temperature and humidity, real-time ventilation volume, and real-time concentration of bacteria and viruses; Obtaining environmental characteristic requirements and generating a second adjustment scheme for the real-time temperature and humidity, the real-time ventilation volume, and the real-time concentration of bacteria and viruses according to the environmental characteristic requirements; Performing dynamic monitoring on the breeding facilities in the target meat duck house through a facility monitoring component to obtain real-time facility characteristics, wherein the real-time facility characteristics include real-time trough information, real-time water tank information, and real-time manure information; Analyzing the real-time trough information, the real-time water tank information, and the real-time manure information to obtain a third adjustment scheme; Adjusting the environment of the target meat duck house according to the first adjustment scheme, the second adjustment scheme, and the third adjustment scheme; Monitoring the real-time blood oxygen level of the meat ducks; Determining whether the real-time blood oxygen level belongs to a predetermined blood oxygen threshold; If not, calling a predetermined control scheme to adjust the environment of the target meat duck house; The method of adjusting the environment of the target meat duck house by calling the predetermined control scheme comprises the following steps: Extracting a first record from the historical meat duck breeding records, wherein the first record includes the first blood oxygen level, the first environmental characteristics, and the first facility characteristics of the first meat ducks; The first environmental characteristics include the first temperature and humidity, the first ventilation volume, and the first concentration of bacteria and viruses; The first facility characteristics include the first trough information, the first water tank information, and the first manure information; Taking the first temperature and humidity, the first ventilation volume, the first concentration of bacteria and viruses, the first trough information, the first water tank information, and the first manure information as independent variables, and taking the first blood oxygen level as a dependent variable; Obtaining the correlation analysis result of the independent variables and the dependent variables, and formulating the predetermined control scheme according to the correlation analysis result.

2. The method of claim 1, wherein, The method of collecting historical meat duck breeding records and analyzing the activity area demand of the meat ducks in the target breeding stage, and generating a first adjustment scheme for the meat duck cages in the target meat duck house according to the activity area demand comprises the following steps: Extracting a second record from the historical meat duck breeding records, wherein the second record refers to the breeding record of the second meat ducks; The second record includes the second body width time sequence, the second body height time sequence, and the second active index time sequence of the second meat ducks in the target breeding stage; Comparatively analyzing the second body width time sequence and the second active index time sequence to obtain the width of the meat duck cage; Comparatively analyzing the second body height time sequence and the second active index time sequence to obtain the height of the meat duck cage; Taking the width and the height of the meat duck cage as adjustment criteria to generate the first adjustment scheme.

3. The method of claim 1, wherein, The analysis of the real-time trough information, the real-time water tank information and the real-time fecal pollution information obtains a third adjustment scheme, comprising: The real-time trough information comprises real-time feed quality; A predetermined feed threshold is obtained, and a feed adjustment scheme is obtained in combination with the real-time feed quality; The real-time water tank information comprises real-time drinking water quality; A predetermined drinking water threshold is obtained, and a drinking water adjustment scheme is obtained in combination with the real-time drinking water quality; The real-time fecal pollution information comprises real-time fecal pollution quality; A predetermined fecal pollution threshold is obtained, and a fecal pollution adjustment scheme is obtained in combination with the real-time fecal pollution quality; The feed adjustment scheme, the drinking water adjustment scheme and the fecal pollution adjustment scheme jointly constitute the third adjustment scheme.

4. The method of claim 3, wherein, Further comprising: The real-time trough information comprises a real-time feed image; The real-time feed image is segmented to obtain a segmented image block set, wherein the segmented image block set comprises M image blocks, and M is an integer greater than 1; A first image block in the M image blocks is extracted, and a discrete cosine transform is performed on the first image block to obtain a first discrete cosine coefficient; The first discrete cosine coefficient comprises a first direct current coefficient and a first alternating current coefficient; According to the first direct current coefficient and the first alternating current coefficient, a first characteristic value of the first image block is calculated; The first characteristic value is added to obtain a characteristic value of the real-time feed image; It is judged whether the characteristic value is within a predetermined characteristic value threshold; If not, a cleaning instruction is issued, and a predetermined feed adjustment scheme is called according to the cleaning instruction; The predetermined feed adjustment scheme is added to the third adjustment scheme.

5. The method of claim 1, wherein, Further comprising: The target meat duck house is inspected based on a preset period to obtain an inspection information list; The inspection information list comprises N dead meat ducks in N inspections, and N≥0; The N dead meat ducks in the N inspections are analyzed to obtain N death causes; The target meat duck house is adjusted based on the N death causes.

6. A system for intelligent adjustment of a shed environment, characterized in that The system is used to execute the method of any one of claims 1 to 5, and the system comprises: A target breeding stage module is used to collect the age of meat ducks in a target meat duck house, and determine a target breeding stage in combination with a preset meat duck stage scheme; A first adjustment scheme module is used to collect historical meat duck breeding records and analyze to obtain the activity area demand of the meat ducks in the target breeding stage, and generate a first adjustment scheme of the meat duck cage in the target meat duck house according to the activity area demand; A real-time environmental feature module is used to dynamically monitor the target meat duck house through an environmental monitoring component to obtain real-time environmental features, wherein the real-time environmental features comprise real-time temperature and humidity, real-time ventilation volume and real-time bacteria and virus concentration; A second adjustment scheme module is used to obtain environmental feature requirements, and generate a second adjustment scheme of the real-time temperature and humidity, the real-time ventilation volume and the real-time bacteria and virus concentration according to the environmental feature requirements; The real-time facility feature module is used for dynamically monitoring a breeding facility in the target meat duck house by a facility monitoring component to obtain real-time facility features, wherein the real-time facility features include real-time trough information, real-time water tank information and real-time manure information; The third adjustment scheme module is used for analyzing the real-time trough information, the real-time water tank information and the real-time manure information to obtain a third adjustment scheme; The implementation environment adjustment module is used for adjusting an environment of the target meat duck house according to the first adjustment scheme, the second adjustment scheme and the third adjustment scheme.

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