5128 results about "Crop livestock" patented technology

The invention provides a livestock breeding risk intelligent assessment method and system based on multi-source data fusion, and the method comprises the steps: collecting livestock individual vital sign data, breeding environment parameters, management behavior data and risk-related historical data through Internet of Things equipment, and carrying out the data preprocessing to form a standardized multi-source data set; extracting risk features of individual, group and environment levels based on the data set, and fusing the risk features to form a multi-dimensional risk feature library; utilizing machine learning to construct a differentiated risk assessment model; analyzing the incidence relation between the risk factor and the actual event through the Bayesian network to calibrate the model; realizing livestock risk grade dynamic division and early warning based on the calibrated risk scoring system; and finally, generating intervention suggestions for risk quantitative evaluation, risk prevention and control decision and loss evaluation. According to the method, accurate evaluation of livestock breeding risks is realized, decision support is provided for breeding safety management, and the method has relatively high application value.

The invention discloses an intelligent livestock breeding traceability method and system, and the method comprises the steps: building an overall framework of the intelligent livestock breeding traceability system based on a micro-service architecture, and employing Spring Cloud Al ibaaba as a micro-service technology stack; livestock physiological data and environmental parameters are collected through Internet of Things equipment, and a livestock electronic file is established; an AI intelligent analysis engine is constructed, and livestock health state evaluation, oestrus prediction and abnormal behavior recognition are achieved; the whole life cycle data of livestock from breeding to selling is recorded based on the block chain technology, and a full-chain traceability system is constructed. The method further comprises the functions of integrating a financial service interface, designing a multi-terminal collaborative application platform, constructing a matchmaking transaction platform and the like. According to the invention, the problems of data islanding, incomplete traceability system, low intelligent level, insufficient system expandability and the like in the prior art are solved, and the accuracy, traceability and system stability of livestock breeding are improved.

The invention discloses a livestock epidemic disease early warning method and system based on big data analysis, and the method comprises the steps: generating a preliminary epidemic situation diffusion path through employing the farm distribution and traffic network data of a geographic information system in combination with a space-time propagation model, and carrying out the dynamic adjustment according to the real-time updated data; predicting a high-risk area by adopting a multi-source data fusion early warning model; the strain mutation risk is judged by analyzing the relevance between pathogen genomes and environmental parameters; deploying a deep learning model at an edge computing node, analyzing animal husbandry behaviors and voiceprint data in real time, and evaluating the animal husbandry health state; and integrating mutation risk analysis and animal husbandry health assessment results to generate a comprehensive epidemic situation early warning report. Through multi-dimensional data analysis and edge intelligent calculation, accurate early warning of animal epidemic situations is realized, and a scientific basis is provided for epidemic situation prevention and control.

The invention relates to the technical field of livestock breeding, in particular to a cow manure automatic scoring system and method.The cow manure automatic scoring system comprises an image acquisition unit, a physical property sensor, a chemical component detection module and a data processing unit.The image acquisition unit is used for capturing the form, color and fiber residue of manure; the physical property sensor is used for measuring the water content of excrement and evaluating the viscosity and hardness of the excrement; the chemical component detection module comprises a near infrared spectrum analysis unit and an electrochemical sensor unit; and the data processing unit is used for integrating an AI algorithm, realizing multi-source data fusion and scoring, and uploading the data to the cloud management platform through the communication module. Therefore, the problems that in the prior art, manual scoring is subjective, low in efficiency and difficult to quantify, diseases are difficult to find early due to the lack of rapid component detection means, and accurate nutrition regulation and control are difficult to achieve due to the fact that scoring data are difficult to integrate into a breeding system are solved.

A livestock management system includes a first type of livestock tag, a second type of livestock tag, and a computing device. The first type of livestock tag includes both a first long-range wireless transceiver and a first short-range wireless transceiver and is attached to a first livestock animal. The second type of livestock tag, which is attached to a second livestock animal, includes second short-range range transceiver that transmits a unique tag identifier associated with the second type of livestock tag to the first short-range wireless transceiver; the second type of livestock tag is incapable of transmitting a long-range wireless transmission. The computing device receives the unique tag identifier of the second type of livestock tag from the first type of livestock tag via long-range wireless transmission from the first long-range wireless transceiver.

The invention relates to the technical field of spectrum water quality detection, in particular to a livestock breeding water quality detection method which comprises the following steps: acquiring absorption spectrum data of a livestock breeding water body, and acquiring a short-time fluctuation difference value of livestock breeding water at each measurement moment on each wave band absorption spectrum; the method comprises the following steps: based on the deviation between short-time fluctuation difference values of livestock breeding water in each wave band and other wave bands, acquiring short-time interference characteristic values of the livestock breeding water in absorption spectra in each wave band at each measurement moment, and combining spectral data differences of each measurement moment and a plurality of previous measurement moments in the same wave band; determining a water quality change coefficient of the absorption spectrum of each wave band; and according to the water quality change coefficient in combination with the short-time interference characteristic value, obtaining a water quality pollution evaluation value of the livestock breeding water at each measurement moment so as to judge the water quality condition of the livestock breeding water. The detection accuracy of the water quality of the livestock breeding water can be improved.

The invention relates to the cross technical field of computers and livestock breeding, and discloses an intelligent nutrition mode management method and system based on HAP multi-modal data, and the method comprises the steps: obtaining the multi-source heterogeneous HAP data of livestock, and carrying out the feature extraction and feature fusion of the multi-source heterogeneous HAP data; utilizing a controllable generative adversarial network to generate enhanced HAP feature data and an HAP feature data sequence simulating a physiological process; early abnormal signals are detected through an abnormal detection algorithm, and multi-modal attribution analysis is carried out; continuously optimizing the nutrition demand prediction model and the feeding strategy optimization model; according to the method, by effectively utilizing the neglected unstructured information in the past and combining the multi-modal fusion analysis, the early-stage discovery capability of the weak signal for indicating the physiological abnormality or nutritional imbalance of the livestock and poultry is improved.

The invention discloses a cattle manure automatic cleaning device and method for a cattle farm, and relates to the technical field of livestock breeding intelligent equipment.The method comprises the steps that a hexagonal monitoring grid is established based on excretion coordinates, a manure accumulation thermodynamic diagram is established through a three-dimensional space point cloud reconstruction method, and according to thermodynamic value intensity distribution in the manure accumulation thermodynamic diagram, the manure accumulation thermodynamic diagram is obtained; marking a to-be-cleaned area; according to the to-be-cleaned area, dynamically analyzing faeces conductivity characteristics by adopting an electromagnetic eddy current detection method, and generating a cattle faeces viscosity index and a cleaning difficulty coefficient through a multi-physics coupling algorithm in combination with environmental parameters; and according to the excrement viscosity index and the cleaning difficulty coefficient, a control instruction set of the cleaning device is generated through a dynamic adjustment algorithm. According to the invention, by constructing the hexagonal monitoring grid and the excrement accumulation thermodynamic diagram, spatial modeling of excrement distribution and intelligent marking of the cleaning area are realized.

The invention discloses a method and a system for controlling disinfection equipment for animal husbandry and veterinary medicine, relates to the technical field of equipment control, and is used for solving the problems that the automation degree of the existing disinfection and killing operation is insufficient, and the disinfection and killing are weak, a plurality of disinfection and killing points are arranged in an animal husbandry farm, and the disinfection equipment, a sensor module and a wireless control terminal are arranged; the sensor module is used for acquiring livestock environment data of a livestock area under each disinfection point, the wireless control terminal is used for inputting the livestock environment data of the respective livestock area, parameter configuration and equipment state detection are carried out on disinfection equipment of the respective livestock area, disinfection operation of the respective livestock area is carried out, and whole-process monitoring is carried out; the method comprises the following steps: acquiring a monitoring result, marking a disinfection weak item of each disinfection device, establishing a respective disinfection fitting model according to the disinfection weak item, executing respective disinfection operation again according to the disinfection fitting model, and pushing a disinfection result of each disinfection point to an animal husbandry veterinary, thereby realizing automatic high-efficiency disinfection.

The invention discloses an intelligent ventilation system and method for a cage for livestock breeding, and belongs to the technical field of livestock breeding, and the system comprises an acquisition processing module, an environment modeling module, a change prediction module, an optimization decision module, a strategy simulation module, a storage safety module, an equipment control module, a monitoring feedback module, a user interaction module and an emergency response module. According to the invention, environmental conditions can be managed more actively, environmental parameters are prevented from deviating from an ideal state due to a hysteresis effect, the stress influence on animals is reduced, specific requirements of different livestock animals are met, the air quality and animal health level in an animal house are improved, the decision precision of the system is improved, and the economic benefit is increased. It is ensured that the cage environment is always kept in the most ideal state, improvement of air quality in a short term and minimization of long-term energy consumption are balanced, and the overall efficiency of the system is effectively optimized.

The invention relates to the technical field of livestock breeding instruments, and discloses an auxiliary fixing device for animal husbandry veterinary examination, which comprises a fixing cage, fences are arranged on the periphery of the fixing cage, a fixing cage base is used as a horizontal plane, for two oppositely arranged fences in the X-axis direction of the fixing cage base, a neck clamping device is arranged in one of the fences, and the neck clamping device is arranged in the other of the fences. One fence is of a movable structure and moves towards the neck clamping device under the action of a driving mechanism, a cage door is formed in the fence, and a lower fixing device is arranged on the lower portion of the fixing cage and used for limiting and supporting the abdomen and four limbs of the livestock. Lifting frames are arranged on the two sides of the outer portion of the fixing cage in the Y-axis direction. The lower fixing device and the upper fixing device are matched with each other, the abdomen, the four limbs and the back of the livestock are limited, supported and clamped in all directions, so that the livestock is difficult to struggle off and keeps a relatively stable posture, and a safe and reliable foundation is provided for subsequent inspection operation.

The invention relates to the technical field of feed screening devices, and particularly discloses a livestock feed screening device which comprises a rotary vibration screen main body, a discharge port and a screen. The device further comprises a feeding hopper. A collection box; a detection mechanism; an adjusting mechanism; according to the livestock feed screening device, the discharging amount of the multiple discharging ports in the unit time is detected through the arranged detection mechanism, and when the detection mechanism detects that the discharging amount of the discharging ports in the unit time is reduced, the falling speed of feed in the feeding hopper is adjusted through the adjusting mechanism; the screening efficiency is affected by accumulation of a large amount of feed on the screens due to more feed and less discharge in the spin-vibration screen main body, and the carding mechanisms respectively comb the screens to prevent feed particles from blocking meshes of the screens to affect the screening efficiency, so that the labor amount of workers is reduced, the workers do not need to stay near the spin-vibration screen main body for a long time, and the working efficiency is improved. And dust generated by vibration is prevented from influencing the health of workers.

The invention relates to the technical field of livestock medicine management and control, in particular to a medicine delivery system based on livestock veterinary epidemic prevention, and the system comprises a data collection and fluctuation rate analysis module which is used for collecting livestock farm environment data and animal health data, aggregating the environment data and the health data layer by layer in a recursive layering manner, and obtaining a multi-level livestock farm data set, calculating the change range of the animal health data in the multi-level data set, determining the range of volatility, and generating abnormal fluctuation mark data. According to the method and the system, the environmental data and the animal health parameters of the livestock farm are subjected to recursive hierarchical aggregation, so that the fluctuation condition of the data is comprehensively monitored. By marking the high fluctuation item with the abnormal fluctuation range exceeding the safety threshold, the potential epidemic disease risk can be quickly identified. By referring to influence factors of high fluctuation items on epidemic disease occurrence and dynamically adjusting risk values, the system can reflect potential influences of changes of environment and health conditions on epidemic disease transmission in real time.

The invention discloses a livestock health state monitoring method, apparatus and device, and a storage medium. The livestock health state monitoring method comprises the steps of obtaining sensor monitoring data in a livestock factory; constructing a sample data set according to the sensor monitoring data; and performing model pre-training and model tuning training on a pre-constructed monitoring network model by adopting the sensor sample data until a preset model training ending condition is met, and taking the trained monitoring network model as a livestock health monitoring model. By means of the technical scheme, the model performance of the livestock health monitoring model applied to different livestock factory areas is improved, and meanwhile the training efficiency of model training is improved.

The invention belongs to the technical field of environment regulation and control, and discloses a livestock breeding environment dynamic prediction and regulation and control method based on machine learning. Comprising the following six key steps: firstly, preprocessing multi-source data, and constructing a standardized feature data set; secondly, performing time sequence feature extraction and environment-biological response correlation analysis to obtain a multi-factor interaction network; then, constructing a dynamic coupling model of the environmental parameters and the production efficiency; a multi-target reinforcement learning regulation and control model is constructed based on the animal husbandry production efficiency prediction space; predictive environmental parameter regulation and risk assessment are carried out in combination with real-time monitoring data; and finally, intelligent environment intervention is executed, and a regulation and control strategy is iteratively optimized through production index feedback. According to the method, the breeding environment is converted from passive response to active prediction, complex correlation understanding between environmental factors and biological indexes is established, and multi-target balance optimization of production efficiency, energy consumption and animal welfare is achieved.

The invention relates to the field of livestock breeding, in particular to a cattle body size performance measurement system based on a binocular camera, which comprises a binocular camera acquisition module, a posture recognition and key point extraction module, a point cloud processing module, a posture correction module and a data processing and optimization module. According to the invention, the binocular camera is combined with an advanced algorithm, so that the measurement efficiency in the cattle breeding process is greatly improved; through cooperative work of multiple modules, reliable data support is provided for cattle breeding; manual measurement is not needed in the whole process, manual operation errors are avoided, the labor intensity of workers is reduced, meanwhile, stress reactions of cattle caused by manual fixing and measurement are reduced, and healthy growth of the cattle and scientization and humanization of breeding management are facilitated; the system can adapt to different light conditions, cattle body types and motion states, can stably and accurately complete body size performance measurement tasks no matter in an indoor breeding environment or in an outdoor pasture environment, and has a wide application prospect.

The invention provides a livestock breeding state monitoring method and system, and relates to the technical field of data processing, and the method comprises the steps: setting an RFID chip and a health monitoring sensor on each animal body; acquiring a multi-modal sensor data sequence of the animal in the time window; preprocessing the sensor data sequence; respectively extracting hidden states of various sensor data sequences through a long-short term memory neural network; based on a self-attention mechanism, adding a self-attention weight to the hidden state at each moment; obtaining intermediate monitoring results corresponding to the various sensor data sequences according to the hidden states and the self-attention weights of the various sensor data sequences; an independent channel is configured for each intermediate monitoring result in the full-connection network; based on a channel attention mechanism, adding a channel attention weight for each channel; and based on the weight of each channel, summarizing various intermediate monitoring results, and determining a comprehensive monitoring result.

Method for controlling livestock functions of a livestock facility including at least one animal box comprising a surface being an endless belt supporting at least one animal and a belt cleaner. The method comprises sensing and obtaining animal environment parameter data using at least one sensor device, collecting animal environment parameter data from the sensor device(s), processing the animal environment parameter data, providing control information using an adaptive trained model of how to control functions of said livestock facility to maximize / optimize at least one animal environment score, determining control commands instructing how to control and adapt livestock functions of the livestock facility based on said processed animal environment parameter data and said control information from said adaptive trained model, and controlling said endless belt and / or belt cleaner by sending control commands thereto in order to maximize / optimize said at least one animal environment score. A corresponding system is also provided.

The invention relates to the technical field of livestock breeding, in particular to an intelligent feed optimal proportioning method based on pig herd nutrition analysis, which comprises the following steps: S1, collecting stress index data of a pig herd; s2, analyzing the stress level and the stress source of the swinery; s3, dynamically adjusting nutritional requirement parameters according to the stress level and the stress source, and determining nutrients needing to be adjusted under different stress conditions; s4, making corresponding stress mitigation measures based on the stress source and the stress intensity; s5, generating an optimal feed formula meeting the nutritional requirements of the swinery under the stress condition; and S6, converting the optimal feed formula into a production instruction, and sending the production instruction to feed production equipment. By dynamically adjusting the nutritional requirements of the swinery under different stress conditions and combining intelligent feed production equipment, precise feed formula optimization and efficient production are achieved, the feed utilization rate and the swinery health level are improved, and meanwhile the breeding cost is reduced.

The invention discloses a poultry multi-stage feed net energy in-vitro prediction method and device based on factorial screening, and relates to the technical field of animal husbandry. The method comprises the following steps: collecting and screening poultry feed raw material samples; analyzing the factors of the raw material components influencing the net energy value by adopting a factorization method to obtain a key component set; based on poultry feed raw material samples, determining the content of key components of each feed raw material and net energy values of the poultry feed raw material samples in different growth stages of poultry; based on the measured content of the key components of each feed raw material and the net energy values of the poultry feed raw material samples in different growth stages of poultry, performing principal component analysis to obtain predictive factors; constructing target net energy prediction equations of different growth stages of the poultry by using a linear regression analysis method based on the prediction factors; and performing net energy prediction on the poultry feed raw materials to be detected based on the target net energy prediction models of different growth stages of the poultry to obtain predicted net energy values of different growth stages of the poultry.

The invention belongs to the technical field of ecology, geographic information system (GIS) and environment management, and discloses a preferential restoration method for an ecological degradation region, which comprises the following steps: acquiring change characteristics of each land utilization type in the region; identifying an ecologically degraded land urgently to be subjected to ecological restoration; estimating the habitat quality of the ecological system in the region, the carbon immobilization service, the grain yield and income in the region, and the animal husbandry yield and income; the economic loss caused by ecological restoration evaluation is obtained; setting a plurality of recovery scenes; and obtaining a restoration strategy of the ecological degradation area based on setting of a plurality of different restoration scenarios, and the like. Compared with a traditional restoration method depending on expert experience and field investigation, the preferential restoration method can scientifically and accurately identify the ecological degradation area to be subjected to ecological restoration through systematic analysis and evaluation, and provides diversified restoration strategy suggestions for decision makers.

The invention relates to the technical field of conveying devices, in particular to a double-cavity feed conveying method for livestock breeding, which comprises the following steps: SS01, arranging and presetting a conveying device, arranging the conveying device at a specified conveying place, and adjusting the conveying stroke of the conveying device according to the conveying height and conveying stroke requirements of feed after the conveying state is arranged, SS02, conveying, when the conveying device works, drying and screening of the feed are synchronously achieved, and the feed is conveyed to the designated height. The double-cavity conveying device has the beneficial effects that when the double-cavity conveying device works, double-cavity conveying of the conveying device can be achieved through the arrangement of the conveying cavity and the discharging guide cavity, and before the double-cavity conveying device achieves double-cavity conveying, the relative positions of the telescopic cylinder and the rotary cylinder and the inner cylinder can be adjusted by driving the lead screw lifting module according to the conveying length requirement, so that the double-cavity conveying device achieves double-cavity conveying. And therefore, the conveying stroke and the conveying height of the conveying device are adjusted, and the application scenes of the conveying device are effectively increased.

The invention relates to the technical field of livestock breeding, and particularly discloses a cleaning device for animal husbandry, the cleaning device comprises a base, a lifting support, a cleaning assembly and an auxiliary wheel assembly, the base is provided with a sliding rail in the vertical direction, the lifting support is slidably installed on the sliding rail, and the cleaning assembly is installed on the lifting support; the auxiliary wheel assembly comprises a driving wheel and a clamping wheel, the driving wheel is installed on the side face, close to the outer wall of the water tank, of the base and connected with a first motor, the first motor drives the driving wheel to rotate on the outer wall of the water tank, the clamping wheel is installed on a rotating support, and the rotating support is hinged to the base. A gear set is arranged at the hinged position of the rotating support and connected with a second motor, the second motor drives the rotating support to rotate, and therefore the clamping wheel is driven to rotate, the driving wheel rotates to drive the cleaning device to move, the driving wheel and the rotating wheel clamp the side wall of the water tank, and the cleaning device is limited relative to the water tank. And the distance between the cleaning device and the inner wall of the water tank during movement can be determined.

The invention provides a dense target detection method based on comparative learning characterization and reinforcement learning decision, which is suitable for dense animal individual detection in a livestock breeding scene. The method comprises the following steps: constructing a dense target detection model comprising a feature encoder, a reinforcement learning decision module and a detection head; the training process is divided into two stages: in the contrast learning characterization stage, an anchor sample, a positive sample and a negative sample are constructed, a first loss function is utilized to optimize a feature encoder, and an optimal feature encoder is obtained; in the reinforcement learning decision-making stage, the feature vector is used as an input state, a decision-making module dynamically selects a threshold lowering, maintaining or improving action, a detection head outputs a detection result in combination with the feature and the action, and parameters of the decision-making module are optimized through a reward function. During detection, after features of a to-be-detected image are extracted through the feature encoder, the optimized decision module selects the optimal action, and finally a detection result is output. The method has relatively high robustness and accuracy.

The invention discloses a full life cycle supervision method for stockbreeding machinery, relates to the related technical field of control systems, and generates a regional discharge target sequence by determining a plurality of regional discharge targets according to a transportation path of an automatic discharge vehicle. And selecting a first discharging target from the regional discharging target sequence, and carrying out discharging speed optimization analysis by taking the minimum deviation from the first discharging target as an expectation to obtain a first optimized discharging speed. Discharging angle optimization analysis is carried out, a first optimized discharging angle is output, and a first optimized discharging parameter is generated in combination with the discharging speed. And continuously carrying out discharging parameter optimization analysis on other discharging targets to generate an optimized discharging parameter sequence, and carrying out discharging error correction on the optimized discharging parameter sequence to obtain an optimal discharging scheme for carrying out automatic discharging control on the cow farm. The technical problems that in the prior art, livestock machinery lacks a dynamic full-life-cycle supervision mechanism, the discharging deviation in the automatic discharging process is large, and the feeding effect is affected are solved.

The invention discloses a livestock and poultry health state intelligent evaluation method based on multi-sensor fusion and an AI prediction model, and belongs to the technical field of livestock breeding, and the method comprises the following steps: setting multiple types of sensors in a livestock and poultry breeding area, collecting multi-source data such as temperature, humidity, carbon dioxide concentration, ammonia gas concentration, illumination intensity, weight and current, and carrying out the analysis of the data; wherein the weight data is obtained through the weighing platform, and the current data is used for sensing the operation state of drinking, ingestion, ventilation or lighting equipment; various types of sensors such as temperature and humidity sensors, carbon dioxide sensors, ammonia gas sensors, illumination sensors, weight sensors and current sensors are deployed in livestock and poultry breeding areas, all-directional data acquisition of environments and behavior states is realized, and dynamic modeling and feature extraction of key behavior nodes are realized by introducing a deep neural network structure of a gating circulation unit and an attention mechanism.

The invention belongs to but not limited to the technical field of animal husbandry statistics, and particularly relates to an alpine meadow yak number calculation method and system based on an unmanned aerial vehicle image, and the method comprises the steps: S1, employing an unmanned aerial vehicle to shoot an orthoimage of a sample plot, and carrying out the statistics of the yak number; s2, splicing the shot images by using Pix4D software, screening a proper sample plot, and respectively counting the quantity of wet cow dung and the quantity of dry cow dung in a visual interpretation mode; and S3, carrying out linear fitting on the obtained data by using Origin 2024b, so as to obtain three relation curves. According to the method for estimating the number of the yaks through statistics of the number of the cow dung in the unmanned aerial vehicle image, the workload of data collection is greatly reduced, and the limitation that the number of the yaks cannot be obtained when the yaks are not grazed in the grassland is avoided. According to the invention, the data acquisition frequency of experimenters is effectively reduced, and the research cost is reduced.

The utility model relates to the technical field of isolation cages, in particular to an isolation cage for animal husbandry and veterinary medicine. Comprising a supporting part and an isolation cage body, the supporting part is detachably connected with the isolation cage body, the middle of the isolation cage body is connected with an operation part, the operation part is slidably connected with the isolation cage body, and a limiting assembly is arranged on the outer side of the isolation cage body and used for limiting the operation part; the supporting part comprises a limiting base and a supporting disc, the supporting disc is rotationally connected with the limiting base, and the supporting disc is detachably connected with the isolation cage body. When livestock enter the isolation cage body, the isolation cage body can be driven to rotate through the supporting part, the livestock rotates along with the isolation cage body, and the illness state of the livestock can be conveniently detected; when the livestock is treated, the operation part can be fixed, the posture of the livestock is adjusted, and examination and treatment are facilitated.

Disclosed is an Artificial Intelligence (AI)-based livestock management system and a livestock management method therefor. According to the inventive concept, it is possible to determine whether the animal has abnormal symptoms by learning the standard livestock stall management data and analyzing the body temperature information and behavior information of livestock from livestock image data obtained in real time from livestock such as cattle, thus giving the manager confidence.

The invention relates to the technical field of air environment detection, in particular to an air environment detection system and method for a livestock farm. The method comprises the following steps: deploying a multi-spectral imaging sensor in a livestock farm, collecting multi-period air spectral data and performing gas component identification to obtain gas component spectral change data, so as to perform phase change condition similarity fitting and microbial activity loss simulation, analyze degradation of microbial decomposition ability, and determine whether the microbial decomposition ability declines or not. Identifying an air deterioration trend; and finally, constructing an air environment detection model by using a strategy gradient algorithm, and uploading the model to a cloud platform for execution so as to realize air environment monitoring. According to the invention, the air environment detection technology is optimized, so that the air environment detection technology is more perfect.