CN115540944A - Monitoring and early warning equipment of internet of things - Google Patents
Monitoring and early warning equipment of internet of things Download PDFInfo
- Publication number
- CN115540944A CN115540944A CN202211209571.7A CN202211209571A CN115540944A CN 115540944 A CN115540944 A CN 115540944A CN 202211209571 A CN202211209571 A CN 202211209571A CN 115540944 A CN115540944 A CN 115540944A
- Authority
- CN
- China
- Prior art keywords
- livestock
- disease
- environment
- poultry
- factory
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 90
- 244000144972 livestock Species 0.000 claims abstract description 201
- 201000010099 disease Diseases 0.000 claims abstract description 117
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 117
- 244000144977 poultry Species 0.000 claims abstract description 102
- 238000009395 breeding Methods 0.000 claims abstract description 61
- 230000001488 breeding effect Effects 0.000 claims abstract description 61
- 238000004458 analytical method Methods 0.000 claims abstract description 31
- 230000007613 environmental effect Effects 0.000 claims abstract description 31
- 238000005516 engineering process Methods 0.000 claims abstract description 24
- 238000001514 detection method Methods 0.000 claims abstract description 23
- 238000003860 storage Methods 0.000 claims abstract description 16
- 238000004891 communication Methods 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims description 37
- 238000000034 method Methods 0.000 claims description 29
- 230000002159 abnormal effect Effects 0.000 claims description 27
- 230000037406 food intake Effects 0.000 claims description 19
- 235000012631 food intake Nutrition 0.000 claims description 19
- 230000005856 abnormality Effects 0.000 claims description 18
- 238000005303 weighing Methods 0.000 claims description 17
- 230000033001 locomotion Effects 0.000 claims description 13
- 238000009423 ventilation Methods 0.000 claims description 11
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 claims description 10
- 230000029087 digestion Effects 0.000 claims description 9
- 235000016709 nutrition Nutrition 0.000 claims description 9
- 230000035764 nutrition Effects 0.000 claims description 9
- RWSOTUBLDIXVET-UHFFFAOYSA-N Dihydrogen sulfide Chemical compound S RWSOTUBLDIXVET-UHFFFAOYSA-N 0.000 claims description 6
- 208000002720 Malnutrition Diseases 0.000 claims description 6
- 235000014113 dietary fatty acids Nutrition 0.000 claims description 6
- 230000003203 everyday effect Effects 0.000 claims description 6
- 229930195729 fatty acid Natural products 0.000 claims description 6
- 239000000194 fatty acid Substances 0.000 claims description 6
- 150000004665 fatty acids Chemical class 0.000 claims description 6
- 229910000037 hydrogen sulfide Inorganic materials 0.000 claims description 6
- 230000001071 malnutrition Effects 0.000 claims description 6
- 235000000824 malnutrition Nutrition 0.000 claims description 6
- 208000015380 nutritional deficiency disease Diseases 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 4
- 208000024891 symptom Diseases 0.000 claims description 4
- 206010047700 Vomiting Diseases 0.000 claims description 3
- 235000021316 daily nutritional intake Nutrition 0.000 claims description 3
- 238000009304 pastoral farming Methods 0.000 claims description 3
- 238000009374 poultry farming Methods 0.000 claims description 3
- 230000008673 vomiting Effects 0.000 claims description 3
- 238000007405 data analysis Methods 0.000 abstract description 5
- 230000011218 segmentation Effects 0.000 abstract description 2
- 229910021529 ammonia Inorganic materials 0.000 description 3
- 239000007789 gas Substances 0.000 description 3
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 208000027954 Poultry disease Diseases 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 238000009360 aquaculture Methods 0.000 description 1
- 244000144974 aquaculture Species 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910002092 carbon dioxide Inorganic materials 0.000 description 1
- 239000001569 carbon dioxide Substances 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000009546 growth abnormality Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K29/00—Other apparatus for animal husbandry
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K29/00—Other apparatus for animal husbandry
- A01K29/005—Monitoring or measuring activity, e.g. detecting heat or mating
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K45/00—Other aviculture appliances, e.g. devices for determining whether a bird is about to lay
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
- A61B2503/40—Animals
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/70—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in livestock or poultry
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Environmental Sciences (AREA)
- Animal Husbandry (AREA)
- Biodiversity & Conservation Biology (AREA)
- Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Birds (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention belongs to the field of livestock breeding, relates to a data analysis technology, and is used for solving the problem that the monitoring and early warning equipment of the existing internet of things technology cannot be used for matching the suitable environment of livestock in combination with the growth state, the disease state and the environmental influence factor of the livestock, in particular to the monitoring and early warning equipment of the internet of things technology, which comprises a livestock monitoring platform, wherein the livestock monitoring platform is in communication connection with a growth detection module, an environment matching module, a disease analysis module, an exception handling module and a storage module; the growth detection module is used for carrying out growth detection on livestock and poultry in the livestock and poultry breeding factory and judging whether the growth state of the livestock and poultry meets the requirement; according to the invention, a matching range is obtained by data analysis in a mode of environmental stage segmentation in combination with the forward coefficient and the disease coefficient, and the matching range is the optimal environmental coefficient range of the livestock breeding factory at the current stage, so that the growth state of livestock is improved through the environment.
Description
Technical Field
The invention belongs to the field of livestock breeding, relates to a data analysis technology, and particularly relates to monitoring and early warning equipment of an internet of things technology.
Background
In order to reduce the growth of diseases in a breeding place, reduce the harm and death caused by livestock and poultry diseases and improve the quality and yield of livestock and poultry along with the change of breeding scale and places in the modern livestock and poultry breeding industry, the environment of the breeding place needs to be monitored, such as indoor and outdoor temperature, humidity, carbon dioxide concentration, oxygen concentration, illumination intensity, atmospheric pressure, harmful gas concentration and the like.
The monitoring and early warning device of the internet of things technology generally monitors and analyzes the growth state of livestock and poultry in a livestock and poultry breeding factory, and timely warns when the growth state of the livestock and poultry is abnormal, however, the existing monitoring and early warning device of the internet of things technology does not have the function of matching the suitable environment of the livestock and poultry by combining the growth state, the disease state and the environmental influence factors of the livestock and poultry, so that the livestock and poultry cannot grow in the most suitable environment.
In view of the above technical problem, the present application proposes a solution.
Disclosure of Invention
The invention aims to provide monitoring and early warning equipment based on the Internet of things technology, which is used for solving the problem that the existing monitoring and early warning equipment based on the Internet of things technology cannot match the suitable environment of livestock and poultry in combination with the growth state, the disease state and the environmental influence factors of the livestock and poultry;
the technical problems to be solved by the invention are as follows: how to provide a monitoring and early warning device of the internet of things technology, which can match the suitable environment of livestock and poultry by combining the growth state, the disease state and the environmental influence factors of the livestock and poultry.
The purpose of the invention can be realized by the following technical scheme:
a monitoring and early warning device of the Internet of things technology comprises a livestock monitoring platform, wherein the livestock monitoring platform is in communication connection with a growth detection module, an environment matching module, a disease analysis module, an abnormality processing module and a storage module;
the growth detection module is used for carrying out growth detection on livestock and poultry in the livestock and poultry breeding factory and judging whether the growth states of the livestock and poultry meet requirements, and sending unqualified growth signals to the abnormal processing module through the livestock and poultry monitoring platform when the growth states of the livestock and poultry do not meet the requirements;
the disease analysis module is used for analyzing diseases of livestock in an animal husbandry breeding factory and continuously judging whether the disease states of the livestock meet requirements or not, and sending a disease unqualified signal to the abnormality processing module through the livestock monitoring platform when the disease states of the livestock do not meet the requirements;
the abnormality processing module receives the growth unqualified signal or the disease unqualified signal and then performs abnormality processing analysis, and judges the reason of abnormal growth or abnormal disease as malnutrition or overhigh odor concentration;
the environment matching module is used for detecting, matching and analyzing the environment of the livestock-raising factory, judging whether the breeding environment of the livestock-raising factory meets the requirements and meanwhile obtaining the matching range, and sending the matching range to the mobile phone terminal of a manager through the livestock-raising monitoring platform.
As a preferred embodiment of the present invention, the specific process of the growth detection module for detecting the growth of the livestock and poultry in the livestock and poultry farming factory includes: weighing the livestock and poultry in the livestock breeding factory every day, marking the weighed weight value as a weight value, marking the weight value obtained by weighing the livestock and poultry the previous day as a weighing value, and comparing the weight value with the weighing value: if the weight value is more than or equal to the weighing value, marking the corresponding livestock and poultry as a forward object; if the weight value is less than or equal to the weighing value, marking the corresponding livestock and poultry as a reverse object.
As a preferred embodiment of the present invention, the process of determining whether the growth status of the livestock and poultry meets the requirements comprises: the ratio of the number value of the forward object to the total number of the livestock and poultry is marked as a forward ratio, a forward threshold value is obtained through a storage module, and the forward ratio is compared with the forward threshold value: if the forward ratio is smaller than the forward threshold, the growth state of the livestock and poultry is judged not to meet the requirement, the growth detection module sends an unqualified growth signal to the livestock monitoring platform, and the livestock monitoring platform sends the unqualified growth signal to the abnormity processing module after receiving the unqualified growth signal; if the forward ratio is larger than or equal to the forward threshold value, the growth state of the livestock and poultry is judged to meet the requirement, and the growth detection module sends a growth qualified signal to the livestock monitoring platform.
As a preferred embodiment of the present invention, the specific process of the disease analysis module for performing disease analysis on livestock in the livestock breeding factory includes: the method comprises the steps of obtaining food intake data, digestion data and movement data of livestock and poultry in a livestock breeding factory, marking the ratio of the sum of the food intake data, the digestion data and the movement data to the total number of the livestock and poultry as a disease ratio, obtaining a disease threshold value through a storage module, comparing the disease ratio with the disease threshold value, and judging whether the disease state of the livestock and poultry meets requirements through a comparison result.
In a preferred embodiment of the present invention, the process of acquiring eating data comprises: the daily food intake of livestock and poultry is collected and is compared with the standard amount of food intake, and the livestock and poultry quantity mark that the food intake is less than the standard amount of food intake is the food intake data, and the livestock and poultry quantity value of digestion data for the phenomenon of vomiting appears, and the acquisition process of motion data includes: the number of exercise steps of the livestock and poultry every day is collected and compared with the step number standard quantity, and the number of the livestock and poultry with the exercise steps smaller than the step number standard quantity is marked as exercise data.
As a preferred embodiment of the present invention, the specific process of comparing the disease ratio with the disease threshold value includes: if the disease ratio is smaller than the disease threshold value, the disease state of the livestock and poultry is judged to meet the requirement, and a disease analysis module sends a disease qualified signal to a livestock monitoring platform; if the disease ratio is larger than or equal to the disease threshold value, the disease state of the livestock and poultry is judged not to meet the requirement, the disease analysis module sends a disease unqualified signal to the livestock monitoring platform, and the livestock monitoring platform sends the disease unqualified signal to the abnormality processing module after receiving the disease unqualified signal.
As a preferred embodiment of the present invention, a specific process of the exception handling module performing exception handling analysis includes: acquiring an ammonia gas concentration value, a hydrogen sulfide concentration value and a volatile fatty acid concentration value of air in the livestock-raising factory, respectively marking the ammonia gas concentration value, the hydrogen sulfide concentration value and the volatile fatty acid concentration value as AQ, LQ and ZF, and obtaining an odor coefficient CQ of the livestock-raising factory by carrying out numerical calculation on the AQ, the LQ and the ZF; obtaining an odor threshold value CQmax through a storage module, and comparing an odor coefficient CQ of the livestock breeding factory with the odor threshold value CQmax: if the odor coefficient CQ is smaller than the odor threshold value CQmax, judging that the reason of abnormal growth or abnormal symptoms is malnutrition, sending a nutrition supply signal to the livestock monitoring platform by the abnormality processing module, and sending the nutrition supply signal to a mobile phone terminal of a manager after the livestock monitoring platform receives the nutrition supply signal; if the odor coefficient CQ is more than or equal to the odor threshold value CQmax, the reason that the growth is abnormal or the disease is abnormal is judged to be that the odor concentration is too high, the odor processing signal is sent to the livestock monitoring platform by the abnormal processing module, and the odor processing signal is sent to the mobile phone terminal of the manager after the livestock monitoring platform receives the odor processing signal.
As a preferred embodiment of the present invention, the specific process of the environment matching module determining whether the cultivation environment of the livestock breeding factory meets the requirement includes: acquiring temperature data WD, humidity data SD and ventilation data TF of the animal husbandry factory, wherein the temperature data WD of the animal husbandry factory is the average air temperature value of the animal husbandry factory on the same day, the humidity data SD of the animal husbandry factory is the average air humidity value of the animal husbandry factory on the same day, and the ventilation data TF of the animal husbandry factory is the average ventilation value of the animal husbandry factory on the same day; obtaining an environmental coefficient HJ of the livestock-raising factory by carrying out numerical calculation on the temperature data WD, the humidity data SD and the ventilation data TF; acquiring an environment threshold HJmax through a storage module, and comparing the environment coefficient HJ with the environment threshold HJmax: if the environmental coefficient HJ is smaller than the environmental threshold HJmax, judging that the breeding environment of the livestock breeding factory meets the requirement, and marking the breeding days as the positive days; if the environmental coefficient HJ is larger than or equal to the environmental threshold HJmax, the breeding environment of the livestock breeding factory is judged not to meet the requirements, and the environment matching module sends an environment adjusting signal to the livestock monitoring platform.
As a preferred embodiment of the present invention, the process of acquiring the matching range includes: obtaining the latest n ring positive days and marking the latest n ring positive days as monitoring objects i, i =1,2, \8230, n, obtaining environment coefficients HJi in the monitoring objects i, respectively marking the maximum values and the minimum values of the environment coefficients of the monitoring objects as HJd and HJx, forming an environment range by the HJd and the HJx, dividing the environment range into a plurality of environment stages, marking the average value of the forward ratio of the ring positive days of which the environment coefficients HJi are positioned in the environment stages as the forward coefficient of the environment stages, respectively marking the maximum values and the minimum values of the environment coefficients corresponding to the environment stages with the maximum values of the forward coefficients as ZX1 and ZX2, marking the average value of the disease ratios of the ring positive days of which the environment coefficients are positioned in the environment stages as disease coefficients, and respectively marking the maximum values and the minimum values of the environment coefficients corresponding to the environment stages with the minimum values of the disease coefficients as BZ1 and BZ2; comparing the values of ZX1, ZX2, BZ1 and BZ2 to obtain a matching range; the environment matching module sends the matching range to the livestock monitoring platform, and the livestock monitoring platform sends the matching range to the mobile phone terminal of a manager after receiving the matching range.
The invention has the following beneficial effects:
1. the growth detection module can be used for detecting and analyzing the growth states of the livestock and poultry, whether the growth states of the livestock and poultry meet the requirements or not is judged according to the quantity ratio of the positive objects in the livestock and poultry, and similarly, the disease analysis module can be used for comprehensively analyzing by combining a plurality of parameters of livestock and poultry breeding and judging whether the disease states of the livestock and poultry meet the requirements or not, so that early warning is timely carried out when the growth states or the disease states are abnormal;
2. the abnormality processing module can monitor and analyze the air quality in the livestock-raising factory, the odor coefficient is obtained by carrying out numerical analysis on the concentration values of a plurality of gases, the causes of growth abnormality or disease abnormality are judged according to the numerical value of the odor coefficient, a targeted solution can be provided for the cause judgment result, and the abnormality processing efficiency is improved;
3. can carry out the detection and analysis and obtain the environmental coefficient to the environment of livestock-raising mill through the environment matching module, whether the numerical value size through the environmental coefficient needs to adjust the environment of livestock-raising mill and judges, whether the mode of cutting apart through the environmental phase combines forward coefficient and disease coefficient to carry out data analysis and obtains the matching range simultaneously, the matching range is the best environmental coefficient scope of current stage livestock-raising mill, and then improve the growth state of beasts and birds through the environment, the matching range is regularly updated simultaneously, for the beasts and birds of different growth stages match not join in marriage corresponding matching range, carry out dynamic adjustment to its aquaculture environment according to the growth state of beasts and birds.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of a system according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a method according to a second embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
As shown in fig. 1, a monitoring and early warning device of internet of things technology, including poultry monitoring platform, poultry monitoring platform communication connection has growth detection module, environmental matching module, disease analysis module, exception handling module and storage module.
The growth detection module is used for carrying out growth detection on livestock and poultry of the livestock and poultry breeding factory: weighing the livestock and poultry in the livestock breeding factory every day, marking the weighed weight value as a weight value, marking the weight value obtained by weighing the livestock and poultry the previous day as a weighing value, and comparing the weight value with the weighing value: if the weight value is more than or equal to the weighing value, marking the corresponding livestock and poultry as a forward object; if the weight value is less than or equal to the weighing value, marking the corresponding livestock and poultry as a reverse object; the ratio of the number value of the forward object to the total number of the livestock and poultry is marked as a forward ratio, a forward threshold value is obtained through a storage module, and the forward ratio is compared with the forward threshold value: if the forward ratio is smaller than the forward threshold, the growth state of the livestock and poultry is judged not to meet the requirement, the growth detection module sends an unqualified growth signal to the livestock monitoring platform, and the livestock monitoring platform sends the unqualified growth signal to the abnormity processing module after receiving the unqualified growth signal; if the forward ratio is larger than or equal to the forward threshold, the growth state of the livestock is judged to meet the requirement, and a growth detection module sends a growth qualified signal to the livestock monitoring platform; the growth states of the livestock and the poultry are detected and analyzed, whether the growth states of the livestock and the poultry meet requirements or not is judged according to the quantity ratio of the positive objects in the livestock and the poultry, and similarly, the disease analysis module can perform comprehensive analysis by combining a plurality of parameters of livestock and poultry breeding, and judges whether the disease states of the livestock and the poultry meet the requirements or not, so that early warning is timely performed when the growth states or the disease states are abnormal.
The disease analysis module is used for carrying out disease analysis on the stock raising of the stock raising factory: obtain the food intake data, the digestion data and the motion data of beasts and birds in the livestock-raising mill, the acquisition process of food intake data includes: the daily food intake of livestock and poultry is collected and is compared with the standard amount of food intake, and the livestock and poultry quantity mark that the food intake is less than the standard amount of food intake is the food intake data, and the livestock and poultry quantity value of digestion data for the phenomenon of vomiting appears, and the acquisition process of motion data includes: acquiring the movement steps of the livestock and poultry every day, comparing the movement steps with step number standard quantity, marking the number of the livestock and poultry with the movement steps smaller than the step number standard quantity as movement data, marking the ratio of the sum of feeding data, digestion data and movement data to the total number of the livestock and poultry as a disease ratio, acquiring a disease threshold value through a storage module, and comparing the disease ratio with the disease threshold value: if the disease ratio is smaller than the disease threshold value, the disease state of the livestock and poultry is judged to meet the requirement, and a disease analysis module sends a disease qualified signal to a livestock monitoring platform; if the disease ratio is larger than or equal to the disease threshold value, the disease state of the livestock is judged not to meet the requirement, the disease analysis module sends a disease unqualified signal to the livestock monitoring platform, and the livestock monitoring platform sends the disease unqualified signal to the abnormality processing module after receiving the disease unqualified signal.
And after receiving the growth unqualified signal or the disease unqualified signal, the abnormity processing module performs abnormity processing analysis: the method comprises the steps of obtaining an ammonia concentration value, a hydrogen sulfide concentration value and a volatile fatty acid concentration value of air in the livestock-raising factory, respectively marking the ammonia concentration value, the hydrogen sulfide concentration value and the volatile fatty acid concentration value as AQ, LQ and ZF, obtaining an odor coefficient CQ of the livestock-raising factory through a formula CQ = alpha 1 AQ + alpha 2 LQ + alpha 3 ZF, wherein the odor coefficient is a numerical value reflecting the comprehensive odor concentration in the air in the livestock-raising factory, and the larger the numerical value of the odor coefficient is, the higher the comprehensive odor concentration in the air in the livestock-raising factory is; wherein alpha 1, alpha 2 and alpha 3 are all proportionality coefficients, and alpha 1 is more than alpha 2 and more than alpha 3 is more than 1; obtaining an odor threshold value CQmax through a storage module, and comparing an odor coefficient CQ of the livestock-raising factory with the odor threshold value CQmax: if the odor coefficient CQ is smaller than the odor threshold value CQmax, judging that the reason of abnormal growth or abnormal symptoms is malnutrition, sending a nutrition supply signal to the stockbreeding monitoring platform by the abnormality processing module, and sending the nutrition supply signal to a mobile phone terminal of a manager after the stockbreeding monitoring platform receives the nutrition supply signal; if the odor coefficient CQ is larger than or equal to the odor threshold value CQmax, judging that the reason of abnormal growth or abnormal symptoms is that the odor concentration is too high, sending an odor treatment signal to the livestock monitoring platform by the abnormality processing module, and sending the odor treatment signal to a mobile phone terminal of a manager by the livestock monitoring platform after receiving the odor treatment signal; the air quality in the livestock-raising factory is monitored and analyzed, the odor coefficient is obtained by carrying out numerical analysis on the concentration values of the plurality of gases, the causes of growth abnormity or disease abnormity are judged according to the numerical value of the odor coefficient, a targeted solution can be provided for the cause judgment result, and the abnormity processing efficiency is improved.
The environment matching module is used for detecting, matching and analyzing the environment of the livestock breeding factory: acquiring temperature data WD, humidity data SD and ventilation data TF of the animal husbandry factory, wherein the temperature data WD of the animal husbandry factory is the average air temperature value of the animal husbandry factory on the same day, the humidity data SD of the animal husbandry factory is the average air humidity value of the animal husbandry factory on the same day, and the ventilation data TF of the animal husbandry factory is the average ventilation value of the animal husbandry factory on the same day; obtaining an environmental coefficient HJ of the livestock breeding factory through a formula HJ = beta 1 × WD + beta 2 × SD-beta 3 × TF, wherein the environmental coefficient is a numerical value reflecting the environmental abnormity degree of the livestock breeding factory, the larger the numerical value of the environmental coefficient is, the higher the environmental abnormity degree of the livestock breeding factory is, beta 1, beta 2 and beta 3 are proportionality coefficients, and beta 1 is more than beta 2 is more than beta 3 is more than 1; acquiring an environment threshold HJmax through a storage module, and comparing the environment coefficient HJ with the environment threshold HJmax: if the environmental coefficient HJ is smaller than the environmental threshold HJmax, judging that the breeding environment of the livestock breeding factory meets the requirement, and marking the breeding days as the positive days; if the environmental coefficient HJ is larger than or equal to the environmental threshold HJmax, the cultivation environment of the livestock-raising factory is judged not to meet the requirements, and the environment matching module sends an environment adjusting signal to the livestock-raising monitoring platform; detecting and analyzing the environment of the livestock-raising factory to obtain an environment coefficient, and judging whether the environment of the livestock-raising factory needs to be adjusted or not according to the numerical value of the environment coefficient; obtaining the latest n ring positive days and marking the latest n ring positive days as monitoring objects i, i =1,2, \8230, n, obtaining environment coefficients HJi in the monitoring objects i, respectively marking the maximum values and the minimum values of the environment coefficients of the monitoring objects as HJd and HJx, forming an environment range by the HJd and the HJx, dividing the environment range into a plurality of environment stages, marking the average value of the forward ratio of the ring positive days of which the environment coefficients HJi are positioned in the environment stages as the forward coefficient of the environment stages, respectively marking the maximum values and the minimum values of the environment coefficients corresponding to the environment stages with the maximum values of the forward coefficients as ZX1 and ZX2, marking the average value of the disease ratios of the ring positive days of which the environment coefficients are positioned in the environment stages as disease coefficients, and respectively marking the maximum values and the minimum values of the environment coefficients corresponding to the environment stages with the minimum values of the disease coefficients as BZ1 and BZ2; comparing the values of ZX1, ZX2, BZ1 and BZ2 to obtain a matching range; the environment matching module sends the matching range to the livestock monitoring platform, and the livestock monitoring platform receives the matching range and then sends the matching range to a mobile phone terminal of a manager; the specific process of comparing the values of ZX1, ZX2, BZ1 and BZ2 comprises the following steps:
if ZX1 is more than or equal to BZ1, more than or equal to ZX2, more than or equal to BZ2, or ZX1, more than or equal to ZX2, more than or equal to BZ1, more than or equal to BZ2, the matching range is formed by BZ1 and ZX 2;
if BZ1 is more than or equal to ZX1, more than or equal to BZ2, more than or equal to ZX2, or BZ1, more than or equal to BZ2, more than or equal to ZX1, more than or equal to ZX2, the matching range is formed by ZX1 and BZ2;
if ZX1 is more than or equal to BZ2 is more than or equal to ZX1, the matching range is formed by BZ1 and BZ2;
if BZ1 is more than or equal to ZX1, more than or equal to ZX2, more than or equal to BZ2, the matching range is formed by ZX1 and ZX 2.
The method comprises the steps of carrying out data analysis by combining a forward coefficient and a disease coefficient in an environment stage segmentation mode to obtain a matching range, wherein the matching range is the optimal environment coefficient range of a livestock breeding factory in the current stage, further improving the growth state of livestock and poultry through the environment, updating the matching range regularly, matching livestock and poultry in different growth stages without corresponding matching ranges, and dynamically adjusting the breeding environment of the livestock and poultry according to the growth state of the livestock and poultry.
Example two
As shown in fig. 2, a monitoring and early warning method of the internet of things technology includes the following steps:
the method comprises the following steps: the method comprises the following steps of carrying out growth detection on livestock and poultry in an animal husbandry factory and judging whether the growth state of the livestock and poultry meets requirements, and sending unqualified growth signals to an exception processing module through an animal husbandry monitoring platform when the growth state of the livestock and poultry does not meet the requirements;
step two: performing disease analysis on livestock in an livestock breeding factory and continuously judging whether the disease states of the livestock meet the requirements, sending unqualified disease signals to an abnormality processing module through a livestock monitoring platform when the disease states of the livestock do not meet the requirements, and timely early warning when the growth state or the disease state is abnormal;
step three: when the growth or the disease is abnormal, abnormal processing analysis is carried out, the reason of the growth or the disease is abnormal is judged to be malnutrition or the odor concentration is too high, a targeted solution can be provided for the reason judgment result, and the abnormal processing efficiency is improved;
step four: the environment of the livestock breeding factory is detected, matched and analyzed, whether the breeding environment of the livestock breeding factory meets the requirements or not is judged, meanwhile, a matching range is obtained, the environment coefficient of the livestock breeding factory is adjusted to be within the matching range on the next breeding day, the matching range is the optimal environment coefficient range of the livestock breeding factory in the current stage, and then the growth state of livestock and poultry is improved through the environment.
A monitoring and early warning device of the Internet of things technology is characterized in that when the monitoring and early warning device works, growth detection is carried out on livestock and poultry in a livestock and poultry breeding factory, whether the growth state of the livestock and poultry meets requirements is judged, and a growth unqualified signal is sent to an abnormal processing module through a livestock and poultry monitoring platform when the growth state of the livestock and poultry does not meet the requirements; analyzing diseases of livestock in an livestock breeding factory, continuously judging whether the disease states of the livestock meet requirements or not, and sending unqualified disease signals to an exception processing module through a livestock monitoring platform when the disease states of the livestock do not meet the requirements; detecting, matching and analyzing the environment of the livestock breeding factory, judging whether the breeding environment of the livestock breeding factory meets the requirements or not, meanwhile, obtaining a matching range, adjusting the environmental coefficient of the livestock breeding factory to be within the matching range on the next breeding day, updating the matching range at regular time, and matching different matching ranges for livestock and poultry in different growth stages.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
The formulas are obtained by acquiring a large amount of data and performing software simulation, and the coefficients in the formulas are set by the technicians in the field according to actual conditions; such as: formula CQ = α 1 aq + α 2 lq + α 3 zf; collecting multiple groups of sample data by technicians in the field and setting a corresponding odor coefficient for each group of sample data; substituting the set odor coefficient and the collected sample data into a formula, forming a ternary linear equation set by any three formulas, screening the calculated coefficients and taking the mean value to obtain values of alpha 1, alpha 2 and alpha 3 which are respectively 6.37, 4.45 and 3.39;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the odor coefficient preliminarily set by a person skilled in the art for each group of sample data; as long as the proportional relation between the parameters and the quantified values is not affected, for example, the odor coefficient is in direct proportion to the value of the ammonia concentration value.
In the description herein, references to the description of "one embodiment," "an example," "a specific example," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (9)
1. The monitoring and early warning device of the Internet of things technology comprises a stock raising monitoring platform, and is characterized in that the stock raising monitoring platform is in communication connection with a growth detection module, an environment matching module, a disease analysis module, an exception handling module and a storage module;
the growth detection module is used for detecting the growth of livestock and poultry in a livestock and poultry breeding factory and judging whether the growth state of the livestock and poultry meets the requirement or not, and sending a growth unqualified signal to the abnormal processing module through the livestock and poultry monitoring platform when the growth state of the livestock and poultry does not meet the requirement;
the disease analysis module is used for analyzing diseases of livestock in an animal husbandry breeding factory and continuously judging whether the disease states of the livestock meet requirements or not, and sending a disease unqualified signal to the abnormality processing module through the livestock monitoring platform when the disease states of the livestock do not meet the requirements;
the abnormality processing module receives the growth unqualified signal or the disease unqualified signal, performs abnormality processing analysis and judges the reason of the growth abnormity or the disease abnormity as malnutrition or overhigh odor concentration;
the environment matching module is used for detecting, matching and analyzing the environment of the livestock breeding factory, judging whether the breeding environment of the livestock breeding factory meets requirements or not, and meanwhile obtaining a matching range, and sending the matching range to a mobile phone terminal of a manager through the livestock monitoring platform.
2. The monitoring and early warning device of the internet of things technology according to claim 1, wherein the specific process of the growth detection module for the livestock and poultry of the livestock and poultry farming factory comprises the following steps: weighing the weights of the livestock and poultry in the livestock and poultry farming factory every day, marking the weighed weight values as weight values, obtaining the weight values of the livestock and poultry weighed in the previous day as weighing values, and comparing the weight values with the weighing values: if the weight value is more than or equal to the weighing value, marking the corresponding livestock and poultry as a forward object; if the weight value is less than or equal to the weighing value, marking the corresponding livestock and poultry as a reverse object.
3. The monitoring and early warning device of the internet of things technology as claimed in claim 2, wherein the process of judging whether the growth state of the livestock and the poultry meets the requirements comprises the following steps: the ratio of the number value of the forward objects to the total number of the livestock and poultry is marked as a forward ratio, a forward threshold value is obtained through a storage module, and the forward ratio is compared with the forward threshold value: if the forward ratio is smaller than the forward threshold value, the growth state of the livestock is judged not to meet the requirements, the growth detection module sends an unqualified growth signal to the livestock monitoring platform, and the livestock monitoring platform sends the unqualified growth signal to the exception handling module after receiving the unqualified growth signal; if the forward ratio is larger than or equal to the forward threshold value, the growth state of the livestock and poultry is judged to meet the requirement, and the growth detection module sends a growth qualified signal to the livestock monitoring platform.
4. The monitoring and early warning device based on the internet of things technology as claimed in claim 3, wherein the concrete process of disease analysis of the stock raising factory by the disease analysis module comprises the following steps: the method comprises the steps of obtaining food intake data, digestion data and movement data of livestock and poultry in a livestock breeding factory, marking the ratio of the sum of the food intake data, the digestion data and the movement data to the total number of the livestock and poultry as a disease ratio, obtaining a disease threshold value through a storage module, comparing the disease ratio with the disease threshold value, and judging whether the disease state of the livestock and poultry meets requirements through a comparison result.
5. The monitoring and early warning device of the internet of things technology according to claim 4, wherein the food intake data acquisition process comprises: the daily food intake of livestock and poultry is collected and is compared with the standard amount of food intake, and the livestock and poultry quantity mark that the food intake is less than the standard amount of food intake is the food intake data, and the livestock and poultry quantity value of digestion data for the phenomenon of vomiting appears, and the acquisition process of motion data includes: the number of exercise steps of the livestock and poultry every day is collected and compared with the step number standard quantity, and the number of the livestock and poultry with the exercise steps smaller than the step number standard quantity is marked as exercise data.
6. The monitoring and early-warning device for the technology of the internet of things as claimed in claim 5, wherein the specific process of comparing the disease ratio with the disease threshold value comprises the following steps: if the disease ratio is smaller than the disease threshold value, the disease state of the livestock and poultry is judged to meet the requirement, and a disease analysis module sends a disease qualified signal to a livestock monitoring platform; if the disease ratio is larger than or equal to the disease threshold value, the disease state of the livestock is judged not to meet the requirement, the disease analysis module sends a disease unqualified signal to the livestock monitoring platform, and the livestock monitoring platform sends the disease unqualified signal to the abnormality processing module after receiving the disease unqualified signal.
7. The monitoring and early warning device of the internet of things technology according to claim 6, wherein the specific process of the exception handling module for exception handling analysis comprises: acquiring an ammonia gas concentration value, a hydrogen sulfide concentration value and a volatile fatty acid concentration value of air in the livestock-raising factory, respectively marking the ammonia gas concentration value, the hydrogen sulfide concentration value and the volatile fatty acid concentration value as AQ, LQ and ZF, and obtaining an odor coefficient CQ of the livestock-raising factory by carrying out numerical calculation on the AQ, the LQ and the ZF; obtaining an odor threshold value CQmax through a storage module, and comparing an odor coefficient CQ of the livestock-raising factory with the odor threshold value CQmax: if the odor coefficient CQ is smaller than the odor threshold value CQmax, judging that the reason of abnormal growth or abnormal symptoms is malnutrition, sending a nutrition supply signal to the livestock monitoring platform by the abnormality processing module, and sending the nutrition supply signal to a mobile phone terminal of a manager after the livestock monitoring platform receives the nutrition supply signal; if the odor coefficient CQ is more than or equal to the odor threshold value CQmax, the reason that the growth is abnormal or the disease is abnormal is judged to be that the odor concentration is too high, the odor processing signal is sent to the livestock monitoring platform by the abnormal processing module, and the odor processing signal is sent to the mobile phone terminal of the manager after the livestock monitoring platform receives the odor processing signal.
8. The monitoring and early warning device of the internet of things technology as claimed in claim 7, wherein the concrete process of the environment matching module for judging whether the cultivation environment of the livestock breeding factory meets the requirement comprises: acquiring temperature data WD, humidity data SD and ventilation data TF of an animal husbandry factory, wherein the temperature data WD of the animal husbandry factory is the average air temperature value of the animal husbandry factory on the day, the humidity data SD of the animal husbandry factory is the average air humidity value of the animal husbandry factory on the day, and the ventilation data TF of the animal husbandry factory is the average ventilation value of the animal husbandry factory on the day; obtaining an environmental coefficient HJ of the livestock-raising factory by carrying out numerical calculation on the temperature data WD, the humidity data SD and the ventilation data TF; obtaining an environment threshold HJmax through a storage module, and comparing the environment coefficient HJ with the environment threshold HJmax: if the environmental coefficient HJ is smaller than the environmental threshold HJmax, judging that the breeding environment of the livestock breeding factory meets the requirement, and marking the breeding days as the positive days; if the environmental coefficient HJ is larger than or equal to the environmental threshold HJmax, the breeding environment of the livestock breeding factory is judged not to meet the requirements, and the environment matching module sends an environment adjusting signal to the livestock monitoring platform.
9. The monitoring and early warning device of the internet of things technology according to claim 8, wherein the obtaining process of the matching range comprises: obtaining the latest n positive days of the ring and marking the current n positive days as monitoring objects i, i =1,2, \8230, n, obtaining environment coefficients HJi in the monitoring objects i, respectively marking the maximum values and the minimum values of the environment coefficients of the monitoring objects as HJd and HJx, forming an environment range by the HJd and the HJx, dividing the environment range into a plurality of environment stages, respectively marking the average value of the positive ratios of the positive days of the ring in which the environment coefficients HJi are positioned in the environment stages as the positive coefficients of the environment stages, respectively marking the maximum values and the minimum values of the environment coefficients corresponding to the environment stages with the maximum values of the positive coefficients as ZX1 and ZX2, marking the average value of the disease ratios of the positive days of the ring in which the environment coefficients are positioned in the environment stages as disease coefficients, and respectively marking the maximum values and the minimum values of the environment coefficients corresponding to the environment stages with the minimum values of the disease coefficients as BZ1 and BZ2; comparing the values of ZX1, ZX2, BZ1 and BZ2 to obtain a matching range; the environment matching module sends the matching range to the livestock monitoring platform, and the livestock monitoring platform sends the matching range to a mobile phone terminal of a manager after receiving the matching range.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211209571.7A CN115540944A (en) | 2022-09-30 | 2022-09-30 | Monitoring and early warning equipment of internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211209571.7A CN115540944A (en) | 2022-09-30 | 2022-09-30 | Monitoring and early warning equipment of internet of things |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115540944A true CN115540944A (en) | 2022-12-30 |
Family
ID=84732457
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211209571.7A Pending CN115540944A (en) | 2022-09-30 | 2022-09-30 | Monitoring and early warning equipment of internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115540944A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118095929A (en) * | 2024-02-01 | 2024-05-28 | 苏州德拓联合智能系统科技有限公司 | Environment-based data collection and analysis system and method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114184229A (en) * | 2021-11-30 | 2022-03-15 | 山东汇能电气有限公司 | Switch cabinet operation environment monitoring system |
| CN114199962A (en) * | 2021-12-16 | 2022-03-18 | 山西农业大学 | Harmful gas analysis and monitoring system used in livestock and poultry house |
| CN114665611A (en) * | 2022-05-25 | 2022-06-24 | 融科能源系统(广东)有限公司 | Power distribution cabinet operation intelligent monitoring management system based on data analysis |
| CN114993387A (en) * | 2022-07-18 | 2022-09-02 | 深圳市联智通达智能有限公司 | Mainboard production and processing supervisory systems based on artificial intelligence |
| CN115015483A (en) * | 2022-05-30 | 2022-09-06 | 仲恺农业工程学院 | Feeding supply analysis processing system based on meat pigeon growth data |
-
2022
- 2022-09-30 CN CN202211209571.7A patent/CN115540944A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114184229A (en) * | 2021-11-30 | 2022-03-15 | 山东汇能电气有限公司 | Switch cabinet operation environment monitoring system |
| CN114199962A (en) * | 2021-12-16 | 2022-03-18 | 山西农业大学 | Harmful gas analysis and monitoring system used in livestock and poultry house |
| CN114665611A (en) * | 2022-05-25 | 2022-06-24 | 融科能源系统(广东)有限公司 | Power distribution cabinet operation intelligent monitoring management system based on data analysis |
| CN115015483A (en) * | 2022-05-30 | 2022-09-06 | 仲恺农业工程学院 | Feeding supply analysis processing system based on meat pigeon growth data |
| CN114993387A (en) * | 2022-07-18 | 2022-09-02 | 深圳市联智通达智能有限公司 | Mainboard production and processing supervisory systems based on artificial intelligence |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118095929A (en) * | 2024-02-01 | 2024-05-28 | 苏州德拓联合智能系统科技有限公司 | Environment-based data collection and analysis system and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111198549B (en) | Poultry breeding monitoring management system based on big data | |
| CN115250950B (en) | Method and system for inspecting livestock and poultry pig farm based on artificial intelligence | |
| CN111766827A (en) | Modern pig breeding base real-time monitoring management system based on big data | |
| CN115540944A (en) | Monitoring and early warning equipment of internet of things | |
| CN114199962B (en) | Harmful gas analysis and monitoring system for livestock and poultry houses | |
| CN106500775A (en) | A kind of effective monitoring of crop growth system | |
| CN107771706B (en) | Sow oestrus detection method and system | |
| CN111831037A (en) | Multipurpose plant environment intelligent control system | |
| CN112325949A (en) | Breeding environment monitoring system | |
| CN118033071B (en) | Aquaculture water quality monitoring system based on artificial intelligence | |
| CN113888011A (en) | Chicken coop internal environment evaluation method based on grey correlation analysis and analytic hierarchy process | |
| Ali et al. | Smart Chicken Farm Monitoring System | |
| CN115979339A (en) | Laying hen breeding environment intelligent supervision system based on big data analysis | |
| Naandam et al. | Hatchability of guinea fowls eggs and performance of keets under the traditional extensive system in Tolon-Kumbungu district of Ghana. | |
| CN115015483B (en) | Feeding, supplying, analyzing and processing system based on meat pigeon growth data | |
| CN110779575A (en) | Animal husbandry monitoring system based on big data platform | |
| CN112506985A (en) | Poultry breeding management system | |
| CN112486230A (en) | Intelligent poultry breeding management system | |
| Farida et al. | Comparative study of broiler chicken performance in closed house and conventional system in North Sumatera | |
| CN114720421B (en) | Near infrared spectrum-based detection method for oat relative feeding value | |
| CN111242797A (en) | Prediction system and method for pigsty environment suitability | |
| CN115328242A (en) | Culture environment intelligent regulation system based on remote control | |
| Eunice et al. | Phenotypic, Physiological and Blood Profile Characterization of Muscovy Ducks (Cairina moschata) In North Central Nigeria | |
| Luan | Research on the Application of Artificial Intelligence and Computer Technology in Agricultural Modernization | |
| CN115859209B (en) | Livestock industry poultry breeding abnormality identification method based on feed consumption data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20221230 |
|
| RJ01 | Rejection of invention patent application after publication |