1578results about "Other apparatus" patented technology

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 intelligent breeding, aims to solve the problems that traditional cattle breeding is inaccurate in monitoring and early warning, extensive in feeding control and insufficient in environment control linkage, and provides a fine management method and system. The method comprises the steps of system initialization and individual binding, multi-dimensional data acquisition, physiological state accurate early warning, dynamic adaptive feeding, environment linkage regulation and control and data statistics optimization. The system correspondingly comprises an individual identification and data acquisition module, an improved physiological state monitoring and early warning module, a dynamic adaptive feeding control module, an environment regulation and control module, a data storage and analysis module and a system operation and maintenance module. Multi-dimensional data are collected through the intelligent neck ring, an individual adaptation algorithm is adopted for early warning of the health state, an exclusive feeding scheme is generated, and the breeding environment is regulated and controlled in a linkage mode. The method and the system improve the health rate and the breeding efficiency of cattle herds, reduce feed waste, and are suitable for large-scale cattle breeding fine management scenes.

The invention discloses a bred animal behavior tracking system and method based on artificial intelligence, and the system comprises six modules which are sequentially connected to achieve data transmission and processing. Video streams, audio streams and infrared thermal imaging data of animals in a breeding scene are obtained through a multi-modal data acquisition device, animal contours are extracted through a dynamic contour anchoring Mamba network processing module, time sequence modeling is carried out, and a behavior dynamic map construction module constructs a behavior dynamic map. The behavior dynamic map deviation evaluation module calculates a characteristic deviation value between real time and a standard map, the intelligent breeding multi-mode space-time engine module fuses space-time information and time sequence characteristics to generate space-time correlation behavior data, and finally the behavior tracking result output module outputs animal real-time behavior categories and movement tracks. According to the invention, the behavior feature extraction precision is improved to reflect the continuous change process of animal behaviors; and the requirements of intelligent breeding on high efficiency, accuracy and deep analysis of animal behavior tracking are met.

The invention discloses a pet behavior analysis system based on AI vision, and the system comprises a perception module which generates a multi-source data stream containing vision, hearing and thermodynamics, and the audio and thermal imaging data are independently stored; and the target detection module is used for embedding a pet variety identification branch by adopting a YOLOv8-XNNCutom model, detecting the pet variety, in a multi-pet scene, combining a DeepSORT algorithm to fuse ReID features and a motion trail, constructing a pet relation graph through a graph neural network GNN, outputting a detection frame sequence with a variety label and a continuous tracking trail, and triggering region position judgment, so that the target detection module is used for detecting the pet variety. When the pet enters a user-defined key area, activating a deep analysis mode; the key point detection module is used for performing feature fusion by adopting an HRNet-W48-3D architecture to generate a pet 3D skeleton key point sequential sequence and a posture thermodynamic diagram; the time sequence behavior analysis module is used for capturing behavior time sequence dependence by utilizing a time-space self-attention mechanism through a TimeSformer-Base model to process a rapid conversion behavior; and the early warning module is used for triggering a predictive alarm for progressive abnormity.

The invention provides a cattle behavior recognition method based on a three-axis attitude angle, and belongs to the technical field of intelligent animal husbandry management. According to the method, three-axis attitude angle signals such as the yaw angle (Yaw), the pitch angle (Pitch) and the roll angle (Roll) of the head of a cattle are collected in real time through a gyroscope sensor arranged in wearable equipment such as a cattle ear tag. The method does not depend on images, accelerometers, microphones or other modalities, only based on attitude angle signals, multiple algorithms such as a time sequence sliding window, frequency domain analysis, weighted scoring, sudden change detection and state transition modeling are utilized, and multiple typical behaviors such as ingestion, rumination, water drinking, bed lying, limping, licking, fright jumping and low activity are recognized. The method is suitable for multiple cattle breeds such as dairy cattle, beef cattle and buffalo, has the advantages of low power consumption, lightweight calculation, low deployment cost, accurate identification and the like, and is convenient for realizing behavior monitoring and health management of large-scale cattle individuals. The algorithm path can be flexibly selected, but a core input signal is only limited to attitude angle data, so that the technical boundary of the patent protection of the method is formed.

The embodiment of the invention discloses a feeding method and device capable of accurately regulating and controlling the feed intake of sows. The method comprises the following steps: identifying an individual identity through an electronic ear tag, and collecting backfat thickness, body condition score and weight data by using an inspection robot; dynamically calling a standard feeding curve based on the fetus number and the body condition score, and finely adjusting the target feed intake in combination with the body weight change trend; a quantitative or interactive feeding mode is adopted in the gestation period, feeding is carried out with different meals of wet mixed feed in the lactation period, and the feed-water ratio is dynamically adjusted; meanwhile, a data closed loop is constructed, a feeding strategy is optimized through big data analysis, and abnormal individuals are visualized. According to the scheme, precise self-adaptive regulation and control of the feeding behavior of the sow in the whole breeding cycle are achieved, and the feed efficiency and the breeding performance are remarkably improved.

A smart cat scratcher and a system for implementing a reward protocol for a smart cat scratcher, and / or methods of manufacturing and / or using the smart cat scratcher and system. The smart cat scratcher is configured to automatically dispense rewards in response to detected scratching activity by a cat. The smart cat scratcher includes a scratching surface, one or more sensors configured to detect the scratching activity, a scratcher controller, and a reward dispenser. The scratcher controller is programmed with a reward protocol that includes a training protocol and a maintenance protocol. The training protocol includes multiple training levels, each with corresponding reward schedules and criteria for graduation. The maintenance protocol includes a partial reinforcement schedule for maintaining established scratching behavior. The smart cat scratcher is configured to communicate with a user terminal to receive input and provide status updates regarding the cat's interaction with the smart cat scratcher.

The invention relates to the technical field of behavior feature recognition, in particular to a beef cattle oestrus state monitoring method based on dynamic gait analysis. According to the method, multi-source data acquisition, such as dynamic gait video and body temperature data, video preprocessing, such as frame extraction, denoising, abnormal frame recognition and restoration, target tracking, dynamic gait characteristic parameter extraction, such as step length, step frequency, step speed, joint angle change and body gravity center offset, and life data acquisition, such as diet, body weight change and drinking water. A large oestrus monitoring and recognition model integrating attitude analysis, behavior analysis, living state analysis and an integration module is constructed, and after training and iterative optimization, accurate judgment of oestrus, non-oestrus and wig oestrus states of beef cattle is achieved in combination with ear tag identity recognition. By monitoring the dynamic gaits and behavior modes of the beef cattle and combining daily life data of the beef cattle, the problem of misjudgment caused by wig oestrus is greatly avoided, and the monitoring accuracy is improved.

The invention provides an intelligent cattle farm feeding management system, which belongs to the technical field of intelligent agriculture and animal husbandry, and comprises a data acquisition module, a data processing module, a control module, a user interface module, a communication module and a storage module. The system obtains cattle farm environment and cattle physiological behavior data in real time through a multi-source sensor and image acquisition equipment, intelligent analysis and decision generation are carried out through algorithms such as machine learning, reinforcement learning and fuzzy logic, and automatic management of functions such as feed feeding, environment regulation and control and health early warning is achieved. The system has the characteristics of comprehensive perception, intelligent decision making and accurate execution, the cattle farm feeding efficiency can be effectively improved, cattle health is guaranteed, and the operation cost is reduced.

The invention discloses a sheep weight and size measuring system and method, and relates to the technical field of animal husbandry breeding intelligent management. Firstly, the invention discloses a sheep weight and body size measuring system, which comprises a PLC (Programmable Logic Controller), a computer, a channel module, a blocking module, an identity recognition module, an entrance module, an image acquisition module, a weighing module and a grouping module, wherein the PLC is in communication connection with the computer. Secondly, the invention discloses a method for measuring the weight and the body size of the sheep, and the method comprises the following steps: S1, driving the sheep into a guide channel at the entrance of the system, and arranging a queue; and S2, a worker starts a blocking module to communicate the recognition channel with the guide channel, and after the first sheep enters the recognition channel, the blocking module is started again to block the space between the recognition channel and the guide channel and block the next sheep. The device has the advantages of automation, high precision and non-contact, so that personal errors and sheep stress are reduced, and the working efficiency is improved.

An automated high throughput screening platform for identification of compounds and genomic constructs having mitochondrial function modulating activity and compounds so identified are provided. Use of such compounds for modulating mitochondrial function are also disclosed. A high-throughput screening method of determining genetic mechanisms of action for therapeutic or toxic agents in genetic or pharmacologic models of disease are also provided.

The utility model discloses a pet intelligent garment, which comprises a garment body and four sleeves, the four sleeves are respectively arranged on two sides of the garment body, posture sensors are arranged in the sleeves to sense postures of pet limbs, a control mainboard and a communication module are arranged in the garment body, and the control mainboard is respectively connected with the posture sensors and the communication module. According to the utility model, the attitude sensor can be fixed on the body of a pet so as to sense the attitude of the pet, and the attitude information, positioning information and the like of the pet are uploaded to the cloud server through the control mainboard and the communication module, so that a user can conveniently obtain the state and position of the pet in real time through equipment such as a mobile phone; the pet management is facilitated; and the interaction experience with the pet is improved.

The invention relates to the technical field of visual search, in particular to a visual search experiment method for head fixing brain imaging. Comprising the following steps: fixing a target object on an experiment table, and training the target object through a display screen to obtain a trained target object; obtaining a target stimulus for an experiment and a target display strategy of the target stimulus in a display screen, the target stimulus being an icon for identification; and executing the target display strategy in the display screen, and obtaining behavioral statistical data and brain region microscopic imaging data of the trained target object based on the execution action of the trained target object. According to the method, the brain region microscopic imaging data of the trained target object can be obtained by executing the target display strategy corresponding to the target stimulation in the display screen, the display strategy of the target stimulation in the display screen is optimized, the motion noise interference of the target object is reduced, the brain region microscopic imaging data with higher quality is obtained, and the accuracy of the brain region microscopic imaging data is improved. And the comprehensiveness and the reliability of an experimental result are improved.

The invention provides a multi-source sensing integrated intelligent feeding scheduling and dieting control method and system for a cowshed, and relates to the technical field of intelligent agricultural control, and the method comprises the steps: collecting cattle physiology, cowshed environment, feed state and equipment operation parameters in real time through a distributed sensing network; a machine learning model fusing a time sequence convolutional network and a self-attention mechanism is utilized to predict an individualized feeding demand and a dieting threshold value, and a feeding-dieting risk map for quantifying health and production risks is generated; simulating an extreme scene based on a digital twinborn model to perform dual consistency check, and generating a robust detailed scheduling scheme; converting the scheme into a control instruction to drive execution equipment, and iteratively optimizing the model and the rule; the system comprises a multi-source sensing data acquisition module, an instruction execution module, a feedback optimization module and the like. According to the method, the accurate and self-adaptive feeding management efficiency of individual cattle in a group is improved, the feed utilization efficiency is effectively improved, and the metabolic disease risk is reduced.

The invention relates to the technical field of intelligent aquaculture or precise aquaculture, in particular to a hippocampus health state intelligent identification method and a hierarchical breeding control system, and the method comprises the steps: collecting time sequence behavior data and breeding environment state data of hippocampus individuals; quantizing the time sequence behavior data to generate behavior characteristics; quantifying the breeding environment state data to generate environment characteristics; generating a dynamic health index in combination with the behavior characteristics and the environment characteristics; generating a pathological risk index based on the dynamic health index; combining the dynamic health index and the pathological risk index to generate a comprehensive seed reservation value index; according to the comprehensive seed reservation value index and a preset grading threshold value, the grade of the hippocampus individuals is determined; generating a sorting control instruction according to the grade; according to the method, intelligent decision making from pure preferential selection to preferential selection and risk avoiding is realized, and the screening efficiency of excellent germplasm is remarkably improved.

The invention discloses a configurable low-power-consumption six-axis inertial sensor sampling method suitable for livestock and poultry, and belongs to the technical field of animal behavior recognition and intelligent breeding. According to the method, by setting an intermittent sampling strategy and combining low-frequency period awakening and a short-time high-frequency data sampling window, behavior recognition data collection of the six-axis inertial sensor under the low-power-consumption condition is achieved. Meanwhile, a sampling template mechanism based on a behavior target is introduced, various sampling parameters can be configured according to the growth stage of the animal, the monitoring requirement and the variety difference, and multi-scene switching application such as oestrus recognition, parturient monitoring and night energy-saving guarding is supported. In addition, the system has an edge recognition capability, and can automatically trigger temporary recollection when detecting that the attitude angle is abnormal, so that the integrity of key behavior data is guaranteed. The method has the advantages of low power consumption, accurate recognition, flexible configuration, high adaptability and the like, and is widely applied to behavior monitoring scenes of bred animals such as dairy cows, pigs, sheep, chickens, ducks, geese and the like.

The invention discloses a pet healthy feeding method and device based on multi-mode recognition and dynamic decision, and relates to the technical field of pet feeding, and the method comprises the steps: carrying out the dual-mode identity recognition through pet image data, and obtaining a pet identity recognition result; performing bioelectrical impedance analysis based on the pet identity recognition result to obtain pet physiological indexes; according to the pet identity recognition result and the pet physiological indexes, dynamic decision making is carried out, and an optimal feeding decision is obtained; a feeding instruction is executed according to the optimal feeding decision, and a pet healthy feeding result is obtained. According to the invention, the problems of feeding conflict, single health monitoring, feeding decision stiffness and the like of a multi-pet family are solved, and unprecedented accurate, intelligent and dynamic pet health management is realized.

The invention relates to the technical field of cattle health assessment, and discloses a cattle health assessment method based on a Transform lightweight model, and the method comprises the following steps: 1, synchronously collecting a visible light video stream and an infrared thermal imaging data stream of a target cattle, processing the visible light video stream to identify, track and obtain a continuous attitude skeleton point coordinate sequence of the target cattle; and 2, based on the continuous attitude skeleton point coordinate sequence, the visible light video stream and the infrared thermal imaging data stream, extracting and generating an attitude feature sequence, a visual feature sequence and a temperature feature sequence. By adopting an evaluation technical scheme based on multi-modal data fusion and automatic analysis, the technical effect of carrying out all-weather, standardized and uninterrupted monitoring on the health state of the cattle is achieved, and compared with the technical scheme of visual evaluation depending on artificial experience in the prior art, the defects that the evaluation result is high in subjectivity and tiny health changes cannot be captured in time are overcome.

The invention relates to the technical field of animal cub culture, in particular to an animal cub culture device for animal husbandry veterinarians, which comprises a culture box, a transparent door plate slidably connected to the culture box, a hollow plate inserted into the culture box, an excrement groove hung at the rear end of the culture box, a diversion groove formed in the lower end in the culture box, and a discharge groove formed in the rear wall of the culture box. The driving assembly is located in the incubator and comprises two movable blocks, the upper ends of the movable blocks are fixedly connected with push blocks, a guide rail is fixedly arranged on the top face of the upper end of the incubator, the upper ends of the two push blocks are slidably connected with the guide rail, and the outer walls of the two sides of each movable block are communicated with a plurality of nozzles. The flushed and disinfected area is dried through hot air, the cleaning effect of excrement of the cubs is improved, excrement residues are reduced, bacterium breeding is reduced, a healthy environment is provided for cub culture, and the morbidity of diarrhea, skin diseases and the like of the cubs is reduced.

The invention discloses an intelligent livestock and poultry ear tag device based on edge calculation and lightweight reasoning, and the device comprises a dynamic sampling module which collects the motion behavior data of livestock and poultry through a three-axis acceleration sensor based on a low-power-consumption sampling mechanism. The local processing module carries out local real-time processing on the collected data by adopting feature screening and a light-weight behavior recognition algorithm based on a TinyML model, and the low-power-consumption transmission module processes the collected data based on a bitmap compression coding form to carry out internal communication transmission, so that wireless data transmission is carried out by a low-power-consumption transmission mechanism based on AI edge calculation; according to the method, a low-power-consumption sampling mechanism and a lightweight algorithm based on a TinyML model are matched with feature screening, so that the power consumption and the calculation amount can be greatly reduced; an AI edge computing architecture is utilized, only key events and features are uploaded, the wireless transmission frequency is reduced, the communication power consumption is reduced, and local intelligent operation in a network disconnection scene is supported.

The invention relates to the technical field of intelligent animal husbandry, and discloses a mutton sheep quantitative intelligent feeding management system based on the Internet of Things. Comprising a multi-modal sensing module, an edge computing gateway, a metabolic efficiency feedback factor computing unit, an individual nutrition digital twin modeling unit, an active disturbance response verification mechanism execution unit, an intelligent feeding terminal and a group knowledge evolution module. According to the system, an individual nutrition digital twinborn modeling unit is adopted and is combined with an online reinforcement learning algorithm, and an accurate feeding decision is generated according to a metabolic efficiency feedback factor and a nutrition elasticity coefficient matrix; and an active disturbance response verification mechanism execution unit applies controllable tiny disturbance when the model is uncertain, and an elastic coefficient matrix is dynamically updated. According to the method, the physiological state of the individual is sensed in real time by using multi-modal data, dynamic closed-loop control based on metabolic efficiency is realized, the cold start problem of the new individual is solved through knowledge distillation, and the feed conversion efficiency and the culture benefit are remarkably improved.

The invention relates to a suckling piglet heat preservation lamp control method, device and equipment and a medium, and the method comprises the steps: carrying out the image recognition of a to-be-recognized pigsty image based on a suckling piglet recognition model, so as to determine whether a suckling piglet exists in a pigsty pigsty image or not, and to determine the lying behavior state of the suckling piglet; whether the number of pigsty columns without suckling piglets in the column of pigsty is equal to the total number of pigsty columns corresponding to the column of pigsty or not is judged, and if not, the inspection regulation and control coefficient of the column of pigsty is calculated and determined according to the lying behavior state of suckling piglets in each pigsty column in the column of pigsty and the number of pigsty columns without suckling piglets; and according to the maximum heating power value of the heat preservation lamp, the inspection regulation and control reference value, the inspection regulation and control coefficient, the environment regulation and control reference value and the environment regulation and control coefficient, calculating and determining the target output power of the heat preservation lamp of the pig house, and inputting the target output power to the heat preservation lamp integrated controller. According to the invention, accurate regulation and control of sensible temperature requirements of suckling piglets of different strains and different day ages are realized.

A pad is disclosed. The pad of the present disclosure comprises: a case having an upper plate; a thermoelectric element disposed inside the case; a plate in contact with the thermoelectric element and disposed below the upper plate; and an electric heating sheet disposed between the plate and the upper plate, wherein the upper surface of the electric heating sheet may be in contact with the upper plate, and the lower surface of the electric heating sheet may be in contact with the plate.

The invention discloses a pet emotion multi-modal recognition and intelligent training decision system and method, and relates to the technical field of artificial intelligence, and the method comprises the steps: synchronously collecting multi-modal data, carrying out cross-modal space-time alignment, carrying out species adaptive emotion recognition, generating a personalized training intervention instruction, executing and feeding back a training effect, and continuously optimizing model parameters. The system comprises a multi-modal data acquisition module, a cross-modal space-time alignment module, a species adaptive emotion recognition module, an individualized training decision engine module, an intelligent execution and feedback module and a long-term learning and model updating module. Through adoption of the technical scheme, the method and the device aim at solving the problem of spatial-temporal dislocation of multi-modal data in the prior art, and can realize improvement of time sequence consistency of emotion recognition, improvement of cross-species generalization ability, establishment of a dynamic feedback loop and continuous adaptation to individual behavior changes of pets.

The invention discloses a non-contact multi-source sensing fusion pet health assessment system and method. The system comprises a data acquisition module, a central processing module, a communication module, a terminal module and a pet wearing device. Some basic data are collected through the pet wearing device, data are collected through a plurality of non-contact sensors of the collection module, all the collected data are fused and integrated through the central processing module, a preset health calculation formula is input, a pet health score is output, and an owner is helped to know the health state of the pet in time.

The utility model discloses a low-power-consumption intelligent necklace for shepherds based on dual-mode energy supply. The low-power-consumption intelligent necklace for the shepherds based on dual-mode energy supply comprises a necklace body, the necklace body is provided with a detachable core unit and a dual-mode energy supply unit, and the core unit is connected with the dual-mode energy supply unit; the core unit is a TPU shell in which a positioning chip, a movable sensor, a microprocessor and a communication module which are connected with one another are packaged, and the dual-mode energy supply unit comprises a flexible solar cell, a ceramic micro generator and a micro battery.

The invention discloses a pet health condition optimization method, a pet feeder and a storage medium, and relates to the technical field of pet feeding, and the method comprises the steps: dynamically collecting two-dimensional image information and three-dimensional depth image information of a target pet through a two-dimensional image collection module and a depth image collection module; according to the three-dimensional depth image information, identifying pet body and weight information, and according to the two-dimensional image information and the three-dimensional depth image information, carrying out comprehensive analysis to obtain pet motion state information; and inputting the pet motion state information and the pet body shape and weight information into a machine learning model, predicting to obtain health assessment information, thereby determining a feeding optimization strategy, and adjusting set parameters in a preset feeding plan according to adjustment parameters in the feeding optimization strategy, so that a feeding module executes a feeding task according to the adjusted set parameters. According to the method, the behavior data of the pet is effectively converted into a targeted health improvement strategy, and the intelligence and accuracy of the pet feeder in the aspect of health management are improved.

The invention discloses a cryptosporidium infection early warning method based on pasture environment and oocyst detection rate analysis, which comprises the following steps: collecting pasture multi-medium environment samples and corresponding parameters, and acquiring oocyst concentration by adopting a real-time quantitative PCR (Polymerase Chain Reaction) and a molecular diagnosis model; analyzing association between the oocysts and environmental factors through an oocyst propagation and environmental dynamics model; a key environment variable weight is determined by using MaxEnt and GloWPa-Crypto algorithms, and an oocyst diffusion path is simulated; and fusing multi-dimensional data to divide risk levels, and outputting the infection risk value and duration of each region through iterative operation. According to the method, through multi-medium sampling, multi-model fusion and multi-data deep fusion, the defects of single data, inaccurate propagation process description and insufficient data fusion in the prior art are overcome, the actual infection risks of different areas of the pasture can be accurately reflected, and a precise basis is provided for prevention and control.

An artificial reef module for marine ecosystem restoration comprises a base having a lattice configuration and one or more poles projecting upwardly from the base and configured to support one or more artificial inhabitation units e.g., made by 3D printing, extrusion, pultrusion, or mold specific clay. The module can be configured with one or more of the artificial inhabitation units mounted on the poles, where each inhabitation unit may comprise a plurality of holes formed therein.

The utility model relates to an animal aerosol preference behavior detection system, and belongs to the technical field of animal behavior detection. The triggering device, the drinking water reward device and the data recording device are arranged in the box body, the at least two aerosol release devices are arranged outside the box body, the triggering device is used for triggering operation of animals, and corresponding effective operation is set for each aerosol release device. The triggering device controls the corresponding aerosol release device to release the corresponding aerosol into the box body when detecting effective operation of the animal and controls the water drinking award device to carry out water drinking awarding on the animal at the same time, and the effective operation of the animal on each aerosol release device is recorded through the data recording device. Therefore, the animal aerosol preference behavior can be detected. Therefore, the animal aerosol preference behavior detection device can effectively detect the animal aerosol preference behavior, and is simple in structure and easy to implement.