2078results about "Other apparatus" patented technology

The present invention introduces a universal AI-powered pet management platform that establishes an entirely new category of technology, transcending conventional pet training systems. This comprehensive system integrates a modular wearable pet device with interchangeable sensors, sophisticated AI processing capabilities, and diverse output modules to create a unified ecosystem for holistic pet care. Unlike traditional training devices focused solely on behavior modification, this platform simultaneously manages multiple domains including real-time health monitoring, environmental safety assessment, emotional well-being analysis, autonomous training, emergency response, and seamless integration with external systems. The platform's universal architecture enables dynamic adaptation across diverse applications from companion animals to service animals, wildlife monitoring, and specialized deployments. By leveraging advanced artificial intelligence models, multimodal communication pathways, and a universal API for third-party integration, the system creates an interconnected technological framework that fundamentally transforms the relationship between pets, technology, and human interaction, rendering isolated pet devices obsolete.

The invention relates to the technical field of target detection, and discloses a pet target detection method and device and a camera, and the method comprises the steps: carrying out the motion triggering collection and image enhancement preprocessing of a front end region of a feeder, and obtaining an enhanced image frame sequence; performing feature extraction of dynamic receptive field adjustment on the enhanced image frame sequence to obtain pet feature descriptors and position information; behavior time sequence feature analysis is executed, and pet behavior sequence feature vectors are obtained; constructing a state transition diagram according to the pet behavior sequence feature vector, and performing time sequence consistency analysis to obtain a pet state judgment result; power management and decision execution are carried out on the feeder based on the pet state judgment result, feeding control under the low-power-consumption condition is achieved, behavior misjudgment caused by posture fluctuation is effectively avoided, the behavior recognition accuracy is improved, the accurate feeding control problem in a multi-pet family is solved, and the user experience is improved.

The invention discloses a pigsty environment regulation and control optimization method and system, and belongs to the technical field of breeding environment management. The system comprises an intelligent sensing module, an environment analysis module, a parameter optimization module and a control management module. The intelligent sensing module is used for collecting pig house environment parameters and live pig physiological parameters through a multi-mode sensor; the environment analysis module is used for constructing a behavior recognition model, analyzing behavior characteristics based on physiological parameters and dividing abnormal regions; the parameter optimization module is used for establishing a physiological environment control model and setting an optimal optimization scheme for each abnormal region; and the control management module is used for generating an environment control instruction according to the optimal optimization scheme and controlling equipment execution. The pig house environment and the pig physiological parameters are collected and intelligently analyzed through the multi-mode sensor, automatic and precise environment optimization management is achieved, and the comfort level and the health level of the pigs are improved.

The invention relates to the technical field of intelligent breeding, and discloses an intelligent hog house monitoring system, which comprises a plurality of agent nodes used for collecting physiological parameters, behavior characteristics and environment data of a hog; the edge calculation module is used for constructing an individual health state vector according to the collected data; the state atlas construction module is used for generating a health state atlas based on a time sequence state vector; the control feedback module is used for driving the environment adjusting equipment when the deviation from the optimal state is judged; the communication and cooperation module is used for exchanging prediction information and state feedback among different agent nodes; the federal learning coordination module carries out aggregation and synchronously updates to the agent node; and the system evolution module is used for adjusting a model structure or control parameters during system-level anomaly detection. A federal learning coordination mechanism is adopted to aggregate and synchronize model parameters uploaded by a plurality of agent nodes, and the technical effects of data local processing and model global optimization are achieved.

The invention relates to the technical field of artificial intelligence, and discloses an intelligent rationing system for pig house feed supply, which comprises the following steps: performing identity recognition on pigs in a feeding area through radio frequency identification tags, and extracting weight, growth cycle and behavior characteristics; based on historical ingestion records, health data and environmental factors, a dynamic nutritional requirement model of the pigs is constructed, and the current feed requirement is predicted in combination with a multi-factor regression algorithm; according to the feed demand result, the feeding amount and the feeding frequency of the corresponding trough are adjusted in real time; dynamically adjusting the power of a conveying motor and the pressure difference of a pipeline section by utilizing a variable-frequency driving control technology; and collecting the ingestion response and the feeding execution state of the pigs, and outputting an updated pig allocation result in combination with online feedback and historical data differences. The feeding device has the advantage that the feeding stability 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 present invention relates to the technical field of a cat toilet, and specifically to a device for cleaning a pet feces automatically and intelligently, including a cat toilet main machine (1), a toilet bin (2) arranged inside the main machine, and a detachable feces collecting bin (4). The toilet bin (2) and the feces collecting bin (4) are communicated to each other. The toilet bin (2) is provided therein with an automatically cleaning feces mechanism. The automatically cleaning feces mechanism is configured to transport the feces in the toilet bin (2) to the feces collecting bin (4). No manual cleaning is required. The feces collecting bin is easy to disassemble. It is more convenient to take out the feces.

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.

A monitoring and / or food / water / medicine control system and method of use of the systems provide that (i) an experimenter at the computer desktop sets the schedule for feeding / fasting (food or water or medicine) the animal according to their need, and the animal's access to food or water or medicine will be set accordingly. This allows animal scientists, experimentalists, and experimenters to fully control animal feeding scenarios; (ii) the experimenter remotely opens and closes the animal's access to food / water / medicine regardless of the pre-set schedule; (iii) the experimenter checks the animal's status via real-time monitoring; (iv) an artificial intelligence system identifies and tracks the animal's location and its activities; and (v) a software module connects the vision unit and feeding mechanism to the experimenter's desktop to provide full control of both the vision unit and the feeding mechanism, to calculate different parameters of the animal's activities, and to report the animal's feeding / fasting history, activity history, and upcoming scheduled feedings.

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.

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 discloses an intelligent livestock necklace system with a self-adaptive adjustment function and a control method. The system comprises a behavior perception control module, a network perception transmission module, a group cooperation module, a strategy optimization module and an energy management module.

The invention belongs to the technical field of pet data acquisition and analysis, and particularly relates to a pet full-life-cycle universal data set framework system which comprises an intelligent necklace, a camera, a microphone array, an intelligent system terminal and an acquisition control system integrated in the intelligent system terminal. Signal output ends of the intelligent necklace, the camera and the microphone array are connected with the intelligent system terminal; the acquisition control system comprises a data annotation system and a data analysis and processing system, and the output end of the data annotation system is connected with the data analysis and processing system; and the intelligent system terminal is used as core equipment for data acquisition and management. According to the scheme, the whole life cycle is fully covered, and comprehensive data support is provided for studying health management, behavior development and the like of the whole life cycle of the pet. Multi-modal data fusion meets the training requirements of the AI model in multi-task scenes such as behavior recognition, health monitoring and emotion recognition, and the accuracy and generalization ability of the model are improved.

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 provides an ewe oestrus detection method and device based on multi-modal feature fusion, and relates to the technical field of livestock behavior monitoring, the method comprises the following steps: acquiring behavior data and audio data of an ewe to obtain a first behavior data set and a first audio data set; inputting the first behavior data set into an ewe behavior recognition model to obtain a second behavior data set, and inputting the first audio data set into an ewe sound detection model to obtain a second audio data set; performing feature extraction on the second behavior data set and the second audio data set to obtain a multi-modal feature fusion data set; and inputting the multi-modal feature fusion data set into an ewe oestrus discrimination model to obtain an ewe oestrus detection result. According to the ewe oestrus detection method based on multi-modal feature fusion, on the basis of fully learning the multi-modal features of the ewe, whether the ewe is oestrus or not is intelligently judged through the ewe oestrus judgment model, and the accuracy and efficiency of ewe oestrus detection are improved.

The invention discloses intelligent pasture livestock health monitoring equipment. The equipment comprises a vital sign monitoring mechanism worn on the legs of livestock, a behavior monitoring mechanism worn on the neck of the livestock and an environment monitoring mechanism vertically extending and arranged on the pasture ground; the vital sign monitoring mechanism comprises a vital sign monitoring fixing ring, a vital sign monitoring supporting shell with an upward opening is connected to the vital sign monitoring fixing ring, and a plurality of body temperature monitoring sensors are connected into the vital sign monitoring supporting shell; a pulse monitoring through hole penetrating in the radial direction of the physical sign monitoring fixing ring is formed in the side face of the physical sign monitoring fixing ring, and a pulse monitor is arranged at the pulse monitoring through hole; the behavior monitoring mechanism comprises a conventional monitoring camera, a high-speed monitoring camera and an infrared monitoring camera; the equipment can accurately collect various physiological data of livestock, such as body temperature, heart rate, respiratory rate and the like, as well as behavior data, such as activity amount, ingestion time, rumination times and the like, so that the accuracy and reliability of the data are ensured, and an accurate basis is provided for evaluating the health condition of the livestock.

The invention provides a captive panda oestrus starting prediction method and system based on machine learning, and relates to the technical field of panda breeding, and the method comprises the steps: obtaining original data; isomerous data stream synchronization is carried out according to the original data, and a synchronized spatio-temporal data matrix is obtained; performing nonlinear interaction relation modeling according to the synchronized spatio-temporal data matrix to construct a spatio-temporal dependency relation graph; performing environment constraint feature dimension reduction according to the space-time dependency graph to obtain a low-dimensional state representation vector; performing oestrus state transition probability calculation according to the low-dimensional state representation vector to generate a probability evolution trajectory; and according to the probability evolution trajectory, turning point identification is carried out, and an estrus starting moment prediction value is output. Through collaborative inflection point detection of progesterone gradient characteristics and an ingestion mutation mode in the probability evolution trajectory, an estrus starting moment prediction value is accurately output, and finally the biological interpretability of estrus critical state evolution of captive pandas is improved.

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 belongs to the technical field of livestock feeding management, and particularly relates to a livestock breeding feeding precise management method and system based on an AI technology. A fixed feeding mode based on a growth stage and a self-adaptive dynamic correction algorithm based on environment deviation and activity fluctuation are fused; a multi-dimensional data-driven feeding amount decision model is constructed, dependence of a single parameter is broken through, accurate feeding can be performed according to real-time monitoring data by adopting a self-adaptive feeding mode when the environment or activity amount fluctuates and deviates, the nutritional requirements of livestock are better met, and the feeding efficiency is improved. When data acquisition is abnormal or the environment and activity amount are stable and appropriate, a fixed feeding mode is adopted, and the fixed feeding mode can be periodically updated according to a self-adaptive feeding mode, so that the feeding accuracy and efficiency are improved, the feed waste is reduced, the stability of feed feeding is guaranteed, and the feeding efficiency is improved. And the feeding effect can be brought into an optimal state.

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.

The embodiments herein disclose an automated leash control device for dogs, which aims to optimize the communication and behavior management between a dog and its handler during walks or training sessions. The device utilizes sensors to monitor leash tension, speed, and distance, coupled with a motorized mechanism for controlling leash extension speed. Additionally, the device integrates with an Innovative E-collar, providing compressed air signaling to alert the dog, thereby enhancing training outcomes.

The invention discloses wearable pet multifunctional physical therapy health equipment and a use method thereof. The wearable pet multifunctional physical therapy health equipment comprises a biocompatible flexible substrate and wearing system, an intelligent moxibustion warm physical therapy module, a multifunctional phototherapy module, a bionic micro-vibration massage module, a vital sign real-time monitoring system, an intelligent control and energy system and an omnibearing safety protection system. A biocompatible flexible substrate and a wearable system are adopted as carriers, multiple modules such as intelligent moxibustion warm physical therapy, multifunctional phototherapy, bionic micro-vibration massage and vital sign real-time monitoring are integrated, cooperative operation is achieved through intelligent control and an energy system, and meanwhile an all-around safety protection system runs through all the time. The integrated design breaks through the limitation that traditional pet physiotherapy equipment is single in function. The device has the core advantages that the accuracy of cross-species treatment is improved, the concealment of the treatment process is guaranteed, and human-pet-medical collaborative management is realized.

The present invention provides a method and a system for monitoring the mobility levels of individual farm animals and accordingly determining their corresponding mobility score. The mobility score may be indicative of the health and / or welfare status of the animals. The present invention processes a 2D video recording obtained from an imaging device to detect the movement of individual animals through a space. The video recording is segmented over a set of individual frames and in each frame the individual instances of the animal appearing in the vide frame are detected. The detected instances of each animal over a number of frames are grouped together. From each detected instance of an individual animal a set of reference points are extracted. The reference points are associated with location on the animal body. The present invention determines the mobility score of each animal by monitoring the relative position between reference points in each frame and the relative position of each reference point across the set of individual frames associated with an animal.

The invention relates to the field of smart home, and particularly provides an air purification device, method and equipment, a storage medium and a product. The device comprises a position detection module, an animal attraction module and an air purification module; the position detection module is used for detecting the real-time position of the target animal; the animal attraction module is used for sending attraction information interested by a target animal, and the attraction information comprises at least one of sound information, light information and smell information; and the air purification module is used for purifying surrounding air according to the real-time position and the attraction information. By means of the device, the effect of improving the efficiency of the air purification process can be achieved.

The invention discloses a pig breeding monitoring and behavior intervention method and system based on improved YOLOv11, and relates to the technical field of intelligent breeding, and the method comprises the steps: collecting video data in a pig house in real time through a camera, carrying out the preprocessing, and extracting a key video frame; an improved YOLOv11 algorithm is adopted to construct a pig behavior detection model, key video frames are input into the model for feature extraction, multi-scale features are fused to enhance the recognition capability, a feature map used for behavior classification is generated, and accurate recognition of pig behaviors is achieved through a detection head; and judging whether a pig fighting behavior occurs in a short period according to the pig microscopic behavior characteristics, if so, triggering fighting early warning, when the pig fighting behavior is detected, triggering an intervention mode, and screening an intervention adjustment method from a management decision library according to the pig behavior state and the environment state. According to the invention, accurate identification and active management of pig behaviors are realized, and the identification capability of pig microscopic behaviors in a complex breeding environment is significantly 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.