Animal room environment intelligent monitoring management system

Abstract

The invention discloses an animal house environment intelligent monitoring management system, and belongs to the technical field of environment supervision. The method is used for solving the technical problems of poor active multi-dimensional supervision processing effect and poor self-adaptive optimization management effect of growth environments of animals of different categories in an existing scheme. The method comprises the following steps: respectively screening and classifying a feeding monitoring processing sequence and a local environment index processing sequence which are subjected to early-stage digital processing combination, and respectively carrying out data processing on abnormal feeding animals and abnormal environment animals which are obtained by classification to obtain a corresponding local environment anomaly degree and an overall environment anomaly degree; the local overall abnormal influence values of different dimensions in the early stage are integrated and calculated to obtain living state identifiers corresponding to different animals, the living state identifiers are subjected to data analysis to obtain living states corresponding to different animals, and targeted environment optimization management is implemented.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental supervision, and in particular to an intelligent monitoring and management system for an animal room environment. Background Art

[0002] Animal houses usually refer to special facilities for raising experimental animals for scientific research, teaching, production and other purposes. Such facilities are designed to provide a suitable living environment for experimental animals, ensure animal health and meet experimental needs.

[0003] When the existing animal house environment monitoring and management program is implemented in the humanities, it is impossible to conduct multi-dimensional monitoring, statistics, processing and analysis of the growth environment of different categories of animals in the animal house, and to adaptively implement targeted optimization management of the growth environment of different categories of animals based on the monitoring and processing results of different dimensions. There are problems such as poor active multi-dimensional supervision and processing effects on the growth environment of different categories of animals, and poor adaptive optimization management effects. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent monitoring and management system for an animal house environment, which is used to solve the technical problems of poor active multi-dimensional supervision and processing effects and poor adaptive optimization management effects of the growth environments of different categories of animals in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An intelligent monitoring and management system for an animal house environment, including a multi-dimensional monitoring and statistical processing module for an animal house environment, which is used to perform multi-dimensional monitoring and statistical processing on the growth environment of different categories of animals in the animal house, and obtain monitoring and processing data of the growth environment of different categories of animals corresponding to different dimensions;

[0007] The animal room environment multi-dimensional monitoring abnormal analysis module is used to conduct multi-dimensional local abnormal processing data impact analysis on the growth environment of different categories of animals in the animal room, integrate the local processing analysis results of different dimensions and implement overall dimensional abnormal impact analysis, and adaptively manage the animal room environment intelligently according to the analysis results;

[0008] Among them, the multi-dimensional local abnormal processing data impact analysis includes the abnormal processing data impact analysis of the feeding dimension and the abnormal processing data impact analysis of the environment dimension;

[0009] Conduct an impact analysis of abnormal processing data in the feeding dimension to obtain the feeding monitoring and processing update sequence corresponding to all abnormally fed animals;

[0010] Conduct an impact analysis of abnormal processing data in the environmental dimension to obtain an updated set of environmental indicator processing sequences corresponding to all abnormal environmental animals;

[0011] The local processing analysis results of different dimensions are integrated and analyzed according to the feeding monitoring processing update sequence and the environmental indicator processing sequence update set, and the animal room environment is intelligently managed adaptively based on the analysis results.

[0012] Preferably, all animals in the animal room are counted and numbered, and the categories corresponding to all animals in the animal room are obtained. When monitoring and counting the feeding dimensions of animals of different categories are implemented, different actual feeding time points and corresponding feeding amounts corresponding to animals of different categories are obtained, and different actual feeding time points TWi and corresponding feeding amounts LWi corresponding to animals of different categories are analyzed by a feeding identification function, and a corresponding feeding identifier WBi is output each time; i is the number of animals of different categories, i={1, 2, 3, ..., n}, and n is a positive integer;

[0013] Among them, the expression of the feeding identification function is In the formula, U1i and U2i are the standard feeding time point range and standard feeding amount range corresponding to different categories of animals respectively;

[0014] The feeding flag contains a value of 0, 1 or 2, indicating that the feeding status of the corresponding category animal is normal, partially abnormal or overall abnormal;

[0015] All feeding identifiers obtained by the corresponding monitoring process are sorted and combined according to the animal number to obtain the feeding monitoring process sequence corresponding to the animal of the corresponding category.

[0016] Preferably, when implementing environmental dimension monitoring statistics for animals of different categories, real-time growth environment parameters of animals of different categories are obtained, and different real-time environmental indicator identifiers HBij in the real-time growth environment parameters are subjected to data analysis through an environmental indicator recognition function to obtain environmental indicator identifiers ZBij corresponding to different real-time environmental indicator identifiers of animals of different categories; j is a different environmental indicator identifier in the growth environment parameters; j={1, 2, 3, ..., m}, where m is a positive integer;

[0017] Among them, the expression of the environmental indicator identification function is: In the formula, Uij is the standard environmental indicator range corresponding to different environmental indicator labels;

[0018] The environmental indicator identifier contains a value of 0 or 1, indicating that the real-time environmental indicator status of the corresponding environmental indicator identifier is normal or abnormal;

[0019] All real-time environmental indicator identifiers corresponding to the environmental indicator identifiers of the animals are arranged and combined in Beijing time order to obtain a local environmental indicator processing sequence;

[0020] All local environmental indicator processing sequences of the animal are sorted and combined to obtain the environmental indicator processing sequence set corresponding to the animal.

[0021] Preferably, when analyzing the impact of abnormal processing data in the feeding dimension on the growth environment of different categories of animals in the animal house, the daily feeding monitoring processing sequence of different categories of animals is obtained, and the feeding monitoring processing sequence is traversed and analyzed, and subsequent processing measures are dynamically implemented;

[0022] If all elements in the feeding monitoring processing sequence are 0, a normal feeding label is generated and prompted;

[0023] If there is an element with a non-zero value in the feeding monitoring processing sequence, a daily feeding abnormality label is generated and the animal is marked as an abnormally fed animal. Calculate and obtain the local feeding abnormality WYi of the abnormally fed animal on that day; where Tyi is the abnormal duration of a single abnormal feeding of the abnormally fed animal, n1 is the total number of single abnormal feeding times of the abnormally fed animal on that day; Lyi is the abnormal feeding difference of a single abnormal feeding of the abnormally fed animal, n2 is the total number of single abnormal feeding amounts of the abnormally fed animal on that day; α is the feeding weight coefficient and is greater than 1.

[0024] Preferably, by feeding a holistic regulatory formula Calculate and obtain the overall feeding abnormality WZi corresponding to the abnormally fed animals; where n3 is the total number of single abnormal feedings of the abnormally fed animals;

[0025] The overall feeding abnormality degrees obtained from all abnormal feeding animal processing are respectively associated with their feeding monitoring processing sequences to obtain a feeding monitoring processing update sequence.

[0026] Preferably, when analyzing the impact of abnormal processing data in the environmental dimension on the growth environment of different categories of animals in the animal house, all local environmental indicator processing sequences in the environmental indicator processing sequence set corresponding to different categories of animals are traversed and analyzed, and subsequent processing measures are dynamically implemented;

[0027] If all elements in the local environmental indicator processing sequence are 0, a normal daily environmental label is generated and prompted;

[0028] If there are elements with values ​​other than 0 in the local environmental indicator processing sequence, a daily environmental anomaly label is generated and the animal is marked as an abnormal environment animal. The duration of the indicator abnormality corresponding to the element with a value other than 0 is obtained and set as the local environmental abnormality degree corresponding to the abnormal environment indicator.

[0029] Preferably, through the overall environmental regulation formula Calculate and obtain the overall environmental abnormality HZi corresponding to the abnormal feeding animals; where Tcj is the different local environmental abnormalities that appear on the day of the abnormal environment animals; m′ is the total number of different abnormal environmental indicator marks that appear on the day of the abnormal environment animals;

[0030] The overall environmental abnormality degrees obtained from all abnormal environmental animal treatments are respectively associated with their environmental indicator treatment sequence sets to obtain an environmental indicator treatment sequence update set.

[0031] Preferably, when the local processing analysis results of different dimensions are integrated and analyzed, the overall feeding abnormality WZi and the overall environmental abnormality HZi of different animals monitored and processed in different dimensions are obtained, and the data are analyzed in turn through the life state recognition function to output the life state identification SZi corresponding to different animals;

[0032] Among them, the expression of the life status recognition function is: In the formula, β is the weight coefficient of the regulatory dimension and is greater than 1; A is the standard value of the living conditions corresponding to all animals;

[0033] The life status indicator contains a value of 0 or 1, indicating whether the life status of the corresponding animal is normal or abnormal;

[0034] Preferably, when determining the living states corresponding to different animals in the animal room according to the living state identifiers, the living state identifiers corresponding to the different numbered animals are analyzed in sequence;

[0035] If the living status indicator is 0, the animal will be associated with a normal living status indicator;

[0036] If the living status indicator is 1, the animal will be associated with a mark indicating abnormal living status, and targeted environmental optimization management will be implemented for all animals with abnormal living status.

[0037] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0038] The present invention monitors, counts and digitally processes data in the feeding dimension and environmental dimension of different categories of animals respectively, and combines the digital processing results of different dimensions to obtain corresponding feeding monitoring processing sequences and environmental indicator processing sequence sets. While achieving active multi-dimensional supervision of the growth environment of different categories of animals, the present invention can also provide reliable local processing data support for subsequent local abnormal processing data impact analysis in different dimensions.

[0039] The present invention screens and classifies the feeding monitoring processing sequence and the local environmental index processing sequence of the previous digital processing combination, and processes the data of the abnormal feeding animals and abnormal environment animals obtained by classification, so as to obtain the corresponding local environmental abnormality and overall environmental abnormality, which can provide reliable environmental dimension processing data support for the subsequent processing and analysis of the animal life status.

[0040] The present invention integrates and calculates the local and overall abnormal impact values ​​of different dimensions in the early stage to obtain the life status identifications corresponding to different animals, obtains the life statuses corresponding to different animals by performing data analysis on the life status identifications and implements targeted environmental optimization management, thereby improving the active multi-dimensional supervision and processing effects of the growth environments of animals of different categories and the adaptive optimization management effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The present invention will be further described below in conjunction with the accompanying drawings.

[0042] Figure 1 The present invention is a flowchart of the operation of an intelligent monitoring and management system for an animal room environment. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] like Figure 1 As shown, the present invention is an intelligent monitoring and management system for an animal room environment, comprising an animal room environment multi-dimensional monitoring statistical processing module and an animal room environment multi-dimensional monitoring abnormality analysis module;

[0045] The animal room environment multi-dimensional monitoring and statistical processing module is used to perform multi-dimensional monitoring and statistics and data processing on the growth environment of different categories of animals in the animal room, and obtain the growth environment monitoring and processing data of different dimensions corresponding to different categories of animals; including:

[0046] Count and number all animals in the animal room, and obtain the corresponding categories of all animals in the animal room. Different categories include but are not limited to rabbits, mice and frogs. When monitoring and counting the feeding dimensions of animals of different categories, obtain different actual feeding time points and corresponding feeding amounts corresponding to animals of different categories. The unit of the time point is accurate to analysis, and the feeding amount is grams. The different actual feeding time points TWi and the corresponding feeding amounts LWi corresponding to animals of different categories are analyzed through the feeding identification function and the corresponding feeding identification WBi is output each time; i is the number of animals of different categories, i={1, 2, 3, ..., n}, and n is a positive integer;

[0047] The actual feeding monitoring corresponding to different categories of animals can be realized based on the existing camera video data combined with the Internet of Things technology. For example, the actual feeding actions and actual feeding time points of different categories of animals can be identified and counted by the camera. The feeding amount can be automatically weighed and automatically uploaded by setting a weight sensor and a network module in the feeding device. The network module can be a wireless network card to realize wireless network communication;

[0048] Among them, the expression of the feeding identification function is In the formula, U1i and U2i are the standard feeding time point range and standard feeding amount range corresponding to different categories of animals, which are determined according to the actual feeding experiment requirements of different categories of animals.

[0049] It should be noted that the feeding identification is used to process the data of different aspects of each feeding of different animals and to digitally represent their single feeding status;

[0050] The feeding flag contains a value of 0, 1 or 2, indicating that the feeding status of the corresponding category animal is normal, partially abnormal or overall abnormal;

[0051] All feeding identifiers obtained by the corresponding monitoring process are sorted and combined according to the animal number to obtain the feeding monitoring process sequence corresponding to the animal of the corresponding category;

[0052] In the embodiment of the present invention, the actual daily feeding time points and corresponding feeding amounts of different animals are digitally processed to obtain corresponding feeding marks, and the daily feeding marks are processed and combined to obtain the corresponding feeding monitoring processing sequences of different animals. This can not only realize the digital representation of the daily feeding status of different animals, but also provide reliable feeding monitoring processing data support for the subsequent integration analysis of abnormal data of different local dimensions of different animals.

[0053] When implementing environmental dimension monitoring and statistics for animals of different categories, the real-time growth environment parameters of animals of different categories are obtained, and different real-time environmental indicator identifiers HBij in the real-time growth environment parameters are analyzed through the environmental indicator identification function to obtain environmental indicator identifiers ZBij corresponding to different real-time environmental indicator identifiers of animals of different categories; j is different environmental indicator identifiers in the growth environment parameters; j = {1, 2, 3, ..., m}, m is a positive integer;

[0054] Specifically, different environmental indicators include but are not limited to temperature, humidity, light and ventilation;

[0055] Among them, the expression of the environmental indicator identification function is: In the formula, Uij is the standard environmental index range corresponding to different environmental index identifiers, which is determined according to the actual feeding experimental requirements of different categories of animals.

[0056] It should be noted that the environmental indicator labels are used to digitally represent the environmental indicator status corresponding to different environmental indicator labels of different animals;

[0057] The environmental indicator identifier contains a value of 0 or 1, indicating that the real-time environmental indicator status of the corresponding environmental indicator identifier is normal or abnormal;

[0058] All real-time environmental indicator identifiers corresponding to the environmental indicator identifiers of the animals are arranged and combined in Beijing time order to obtain a local environmental indicator processing sequence;

[0059] All local environmental indicator processing sequences of the animal are sorted and combined to obtain a set of environmental indicator processing sequences corresponding to the animal;

[0060] In the embodiment of the present invention, by monitoring, counting and digitally processing data in the feeding dimension and the environmental dimension of animals of different categories respectively, and combining the digital processing results of different dimensions respectively to obtain corresponding feeding monitoring processing sequences and environmental indicator processing sequence sets, active multi-dimensional supervision of the growth environment of animals of different categories is achieved, and reliable local processing data support can also be provided for subsequent local abnormal processing data impact analysis of different dimensions.

[0061] The animal room environment multi-dimensional monitoring abnormal analysis module is used to conduct multi-dimensional local abnormal processing data impact analysis on the growth environment of different categories of animals in the animal room, integrate the local processing analysis results of different dimensions and implement overall dimensional abnormal impact analysis, and adaptively manage the animal room environment intelligently according to the analysis results; including:

[0062] When analyzing the impact of abnormal processing data in the feeding dimension on the growth environment of different categories of animals in the animal house, obtain the daily feeding monitoring processing sequence of different categories of animals, traverse and analyze the feeding monitoring processing sequence, and dynamically implement subsequent processing measures;

[0063] If all elements in the feeding monitoring processing sequence are 0, a normal feeding label is generated and prompted;

[0064] If there is an element with a non-zero value in the feeding monitoring processing sequence, a daily feeding abnormality label is generated and the animal is marked as an abnormally fed animal. Calculate and obtain the local feeding abnormality WYi of the abnormally fed animal on that day; where Tyi is the abnormal duration of a single abnormal feeding of the abnormally fed animal, by calculating the difference between the actual feeding time point of the abnormally fed animal and the maximum value of the corresponding standard feeding time point range, n1 is the total number of single abnormal feeding times of the abnormally fed animal on that day; Lyi is the abnormal feeding difference of a single abnormal feeding of the abnormally fed animal, which can be negative or positive, and n2 is the total number of single abnormal feeding amounts of the abnormally fed animal on that day; α is the feeding weight coefficient and is greater than 1. The specific value is not limited and is customized according to the application requirements of the actual application scenario;

[0065] It should be noted that the local feeding abnormality is used to digitally represent the abnormal feeding effect of a single abnormal feeding in abnormally fed animals;

[0066] As well as, by feeding the holistic regulatory formula Calculate and obtain the overall feeding abnormality WZi corresponding to the abnormally fed animals; where n3 is the total number of single abnormal feedings of the abnormally fed animals;

[0067] It should be noted that the overall feeding abnormality is used to numerically represent the abnormal feeding impact of overall abnormal feeding in abnormally fed animals;

[0068] The overall feeding abnormality degrees obtained from all abnormal feeding animal processing are respectively associated with their feeding monitoring processing sequences to obtain a feeding monitoring processing update sequence;

[0069] In the embodiment of the present invention, by screening and classifying the feeding monitoring processing sequence of the previous digital processing combination, and processing the abnormal feeding impact corresponding to the single abnormal feeding and the overall abnormal feeding of the abnormally fed animals obtained by classification, the corresponding local feeding abnormality and the overall feeding abnormality are obtained, which can provide reliable feeding dimension processing data support for the subsequent processing and analysis of the animal life status;

[0070] When analyzing the impact of abnormal processing data in the environmental dimension on the growth environment of different categories of animals in the animal house, all local environmental indicator processing sequences in the environmental indicator processing sequence set corresponding to different categories of animals are traversed and analyzed, and subsequent processing measures are dynamically implemented;

[0071] If all elements in the local environmental indicator processing sequence are 0, a normal daily environmental label is generated and prompted;

[0072] If there is an element with a non-zero value in the local environment indicator processing sequence, a daily environment abnormality label is generated and the animal is marked as an abnormal environment animal. The duration of the indicator abnormality corresponding to the element with a non-zero value is obtained and set as the local environment abnormality corresponding to the abnormal environment indicator.

[0073] and, through the overall environmental regulation formula Calculate and obtain the overall environmental abnormality HZi corresponding to the abnormal feeding animals; where Tcj is the different local environmental abnormalities that occur on the day of the abnormal environment animal, and the corresponding unit is minute; m′ is the total number of different abnormal environmental indicator marks that occur on the day of the abnormal environment animal;

[0074] It should be noted that the overall environmental abnormality is used to digitally represent the abnormal environmental impact of the overall abnormal environment of the abnormal environment animals;

[0075] The overall environmental abnormality degrees obtained by processing all abnormal environmental animals are respectively associated with their environmental indicator processing sequence sets to obtain an environmental indicator processing sequence update set;

[0076] In the embodiment of the present invention, by screening and classifying the local environment index processing sequence of the previous digital processing combination, and processing the abnormal environment impact corresponding to the single abnormal environment and the overall abnormal environment for the abnormal environment animals obtained by classification, the corresponding local environment abnormality and overall environment abnormality are obtained, which can provide reliable environmental dimension processing data support for the subsequent processing and analysis of the animal's living status;

[0077] When integrating and analyzing the local processing analysis results of different dimensions, the overall feeding abnormality WZi and overall environmental abnormality HZi of different animals monitored and processed in different dimensions are obtained, and the data are analyzed in turn through the life state identification function to output the life state identification SZi corresponding to different animals;

[0078] Among them, the expression of the life status recognition function is: In the formula, β is the weight coefficient of the regulatory dimension and is greater than 1. The specific value is not limited and is customized according to the application requirements of the actual application scenario; A is the standard value of the living status corresponding to all animals, which is determined according to the actual feeding experiment requirements of different categories of animals;

[0079] It should be noted that the living status identification is used to integrate and calculate the overall abnormal impact values ​​of different dimensions of animals to digitally represent their living status;

[0080] The life status indicator contains a value of 0 or 1, indicating whether the life status of the corresponding animal is normal or abnormal;

[0081] When determining the living status corresponding to different animals in the animal room according to the living status identification, the living status identification corresponding to the different numbered animals is analyzed in turn;

[0082] If the living status indicator is 0, the animal will be associated with a normal living status indicator;

[0083] If the living status indicator is 1, the animal will be associated with a mark indicating abnormal living status, and targeted environmental optimization management will be implemented for all animals with abnormal living status;

[0084] Among them, environmental optimization management includes feeding optimization management and environmental optimization management.

[0085] In the embodiment of the present invention, the local and overall abnormal impact values ​​of different dimensions in the early stage are integrated and calculated to obtain the life status identifications corresponding to different animals, and the life statuses corresponding to different animals are obtained by performing data analysis on the life status identifications and implementing targeted environmental optimization management, thereby improving the active multi-dimensional supervision and processing effects of the growth environments of animals of different categories and the adaptive optimization management effects.

[0086] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0087] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0088] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0089] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0090] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An intelligent monitoring and management system for animal room environment, characterized in that: It includes a multi-dimensional monitoring and statistical processing module for the animal room environment, which is used to perform multi-dimensional monitoring and statistics and data processing on the growth environment of different categories of animals in the animal room, and obtain the monitoring and processing data of the growth environment of different categories of animals in different dimensions; The animal room environment multi-dimensional monitoring abnormal analysis module is used to conduct multi-dimensional local abnormal processing data impact analysis on the growth environment of different categories of animals in the animal room, integrate the local processing analysis results of different dimensions and implement overall dimensional abnormal impact analysis, and adaptively manage the animal room environment intelligently according to the analysis results; Among them, the multi-dimensional local abnormal processing data impact analysis includes the abnormal processing data impact analysis of the feeding dimension and the abnormal processing data impact analysis of the environment dimension; Conduct an impact analysis of abnormal processing data in the feeding dimension to obtain the feeding monitoring and processing update sequence corresponding to all abnormally fed animals; Conduct an impact analysis of abnormal processing data in the environmental dimension to obtain an updated set of environmental indicator processing sequences corresponding to all abnormal environmental animals; The local processing analysis results of different dimensions are integrated and analyzed according to the feeding monitoring processing update sequence and the environmental indicator processing sequence update set, and the animal room environment is intelligently managed adaptively based on the analysis results.

2. The intelligent monitoring and management system for animal room environment according to claim 1 is characterized in that: Count and number all animals in the animal room, obtain the corresponding categories of all animals in the animal room, and when monitoring and counting the feeding dimensions of animals of different categories, obtain the different actual feeding time points and corresponding feeding amounts corresponding to animals of different categories, and perform data analysis on the different actual feeding time points TWi and corresponding feeding amounts LWi corresponding to animals of different categories through the feeding identification function and output the corresponding feeding identification WBi each time; i is the number of animals of different categories, i={1, 2, 3, ..., n}, and n is a positive integer; Among them, the expression of the feeding identification function is In the formula, U1i and U2i are the standard feeding time point range and standard feeding amount range corresponding to different categories of animals respectively; The feeding flag contains a value of 0, 1 or 2, indicating that the feeding status of the corresponding category animal is normal, partially abnormal or overall abnormal; All feeding identifiers obtained by the corresponding monitoring process are sorted and combined according to the animal number to obtain the feeding monitoring process sequence corresponding to the animal of the corresponding category.

3. The intelligent monitoring and management system for animal room environment according to claim 2 is characterized in that: When implementing environmental dimension monitoring and statistics for animals of different categories, the real-time growth environment parameters of animals of different categories are obtained, and different real-time environmental indicator identifiers HBij in the real-time growth environment parameters are analyzed through the environmental indicator identification function to obtain environmental indicator identifiers ZBij corresponding to different real-time environmental indicator identifiers of animals of different categories; j is different environmental indicator identifiers in the growth environment parameters; j = {1, 2, 3, ..., m}, m is a positive integer; Among them, the expression of the environmental indicator identification function is: In the formula, Uij is the standard environmental indicator range corresponding to different environmental indicator labels; The environmental indicator identifier contains a value of 0 or 1, indicating that the real-time environmental indicator status of the corresponding environmental indicator identifier is normal or abnormal; All real-time environmental indicator identifiers corresponding to the environmental indicator identifiers of the animals are arranged and combined in Beijing time order to obtain a local environmental indicator processing sequence; All local environmental indicator processing sequences of the animal are sorted and combined to obtain the environmental indicator processing sequence set corresponding to the animal.

4. The intelligent monitoring and management system for animal room environment according to claim 3 is characterized in that: When analyzing the impact of abnormal processing data in the feeding dimension on the growth environment of different categories of animals in the animal house, obtain the daily feeding monitoring processing sequence of different categories of animals, traverse and analyze the feeding monitoring processing sequence, and dynamically implement subsequent processing measures; If all elements in the feeding monitoring processing sequence are 0, a normal feeding label is generated and prompted; If there is an element with a non-zero value in the feeding monitoring processing sequence, a daily feeding abnormality label is generated and the animal is marked as an abnormally fed animal. Calculate and obtain the local feeding abnormality WYi of the abnormally fed animal on that day; where Tyi is the abnormal duration of a single abnormal feeding of the abnormally fed animal, n1 is the total number of single abnormal feeding times of the abnormally fed animal on that day; Lyi is the abnormal feeding difference of a single abnormal feeding of the abnormally fed animal, n2 is the total number of single abnormal feeding amounts of the abnormally fed animal on that day; α is the feeding weight coefficient and is greater than 1.

5. The intelligent monitoring and management system for animal room environment according to claim 4, characterized in that: By feeding the holistic regulatory formula Calculate and obtain the overall feeding abnormality WZi corresponding to the abnormally fed animals; where n3 is the total number of single abnormal feedings of the abnormally fed animals; The overall feeding abnormality degrees obtained from all abnormal feeding animal processing are respectively associated with their feeding monitoring processing sequences to obtain a feeding monitoring processing update sequence.

6. The intelligent monitoring and management system for animal room environment according to claim 5, characterized in that: When analyzing the impact of abnormal processing data in the environmental dimension on the growth environment of different categories of animals in the animal house, all local environmental indicator processing sequences in the environmental indicator processing sequence set corresponding to different categories of animals are traversed and analyzed, and subsequent processing measures are dynamically implemented; If all elements in the local environmental indicator processing sequence are 0, a normal daily environmental label is generated and prompted; If there are elements with values ​​other than 0 in the local environmental indicator processing sequence, a daily environmental anomaly label is generated and the animal is marked as an abnormal environment animal. The duration of the indicator abnormality corresponding to the element with a value other than 0 is obtained and set as the local environmental abnormality degree corresponding to the abnormal environment indicator.

7. The intelligent monitoring and management system for animal room environment according to claim 6, characterized in that: Through the overall environmental regulation formula Calculate and obtain the overall environmental abnormality HZi corresponding to the abnormal feeding animals; where Tcj is the different local environmental abnormalities that appear on the day of the abnormal environment animals; m′ is the total number of different abnormal environmental indicator marks that appear on the day of the abnormal environment animals; The overall environmental abnormality degrees obtained from all abnormal environmental animal treatments are respectively associated with their environmental indicator treatment sequence sets to obtain an environmental indicator treatment sequence update set.

8. The intelligent monitoring and management system for animal room environment according to claim 7, characterized in that: When integrating and analyzing the local processing analysis results of different dimensions, the overall feeding abnormality WZi and overall environmental abnormality HZi of different animals monitored and processed in different dimensions are obtained, and the data are analyzed in turn through the life state identification function to output the life state identification SZi corresponding to different animals; Among them, the expression of the life status recognition function is: In the formula, β is the weight coefficient of the regulatory dimension and is greater than 1; A is the standard value of the living conditions corresponding to all animals; The living status flag includes a value of 0 or 1, indicating whether the living status of the corresponding animal is normal or abnormal.

9. The intelligent monitoring and management system for animal room environment according to claim 8, characterized in that: When determining the living status corresponding to different animals in the animal room according to the living status identifiers, the living status identifiers corresponding to the different numbered animals are analyzed in turn; If the living status indicator is 0, the animal will be associated with a normal living status indicator; If the living status indicator is 1, the animal will be associated with a mark indicating abnormal living status, and targeted environmental optimization management will be implemented for all animals with abnormal living status.

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