20 results about "Animal data" patented technology

The invention discloses an intelligent animal epidemic disease monitoring management and early warning workstation, which comprises a multi-modal data acquisition module, an epidemic disease risk assessment module, a dynamic early warning threshold generation and judgment module, a visual human-computer interaction interface and a block chain storage module, the multi-modal data acquisition module is used for acquiring animal data of each monitoring point in a preset monitoring area and environment data of animals; the epidemic disease risk assessment module is used for comprehensively analyzing the animal data and the data of the environment where the animals are located to obtain epidemic disease risk indexes of all monitoring points in the current monitoring area; the dynamic early warning threshold generation module is used for dynamically generating an early warning threshold and judging an epidemic disease risk index to obtain an epidemic disease risk level and an epidemic disease risk area; the visual human-computer interaction interface is used for displaying the epidemic disease risk condition in the monitoring area; and the block chain storage module is used for data storage. According to the invention, the accuracy and timeliness of early warning of epidemic diseases are improved.

The present disclosure relates to a method for determining a skin lesion score for a companion animal using an evaluation module trained based on previously acquired metadata associated with the companion animal selected from a data set having at least animal data and skin area data, the method comprises at least the steps of: receiving metadata relating to a companion animal, including two or more items of animal data and two or more items of skin area data listed in a data set; encoding the metadata into a metadata vector; running the trained evaluation module on the metadata vector based on the analysis of the evaluation module on the metadata vector; generating a skin lesion score indicative of a skin condition of the companion animal; and assessing whether the companion animal has an atopic dermatitis condition based on a skin lesion score indicative of at least one skin condition of the companion animal.

The invention discloses a cross-species animal posture estimation method based on an animal behavior monitoring technology, and belongs to the technical field of artificial intelligence and computer vision. In order to solve the problems that in the prior art, cross-species attitude estimation is poor in complex scene robustness, low in system integration level, insufficient in adaptability and real-time performance and the like, the invention provides a cross-species animal attitude estimation method based on an animal behavior monitoring technology, and the method comprises the following steps: collecting image data of a multi-species target animal; preprocessing the image data to obtain a processed animal image; performing cross-species key point configuration and labeling on the image data set to obtain a cross-species animal data set; and performing multi-level feature extraction and fusion on the cross-species animal data set, and realizing a posture estimation result of the target animal based on the fused features. The method is suitable for the fields of wild animal protection, livestock breeding management, animal behavior research, health monitoring, disease prevention and control and the like.

The invention discloses a pest control method and system for forest cultivation, and relates to the technical field of pest control. The method comprises the following steps: acquiring initial monitoring data of forest insect pests, extracting nutrient information of the insect pests, and selecting monitoring plants; collecting monitoring plant data of the forest, and comparing the initial monitoring data with the monitoring plant data to obtain plant growth data; acquiring forest growth information, and evaluating to obtain a primary control effect of forest pests; acquiring real-time animal data of the forest, and comparing the initial monitoring data with the real-time animal data to obtain animal distribution information; evaluating according to the animal distribution information and the forest growth information to obtain an intermediate control effect of forest pests; the pest control effect is confirmed by combining the primary control effect and the intermediate control effect, and pest control is optimized and adjusted to obtain a new pest control scheme. The convenience of pest control for forest cultivation is improved.

The present invention provides a drone data collection method, system, computer equipment and medium. By generating an animal data acquisition path that traverses preset data acquisition points in a monitoring area, and having the drone fly along the animal data acquisition path and then arrive at the data acquisition point to determine whether data acquisition is needed, the method eliminates the need for manual data acquisition at each data acquisition point, thereby reducing the workload and labor costs of data recovery. At the same time, since the drone does not need to be required to operate in an area covered by mobile communication signals when acquiring data, the requirements for mobile communication signal coverage and maintenance in the monitoring area are reduced. This solves the problems in the prior art of manual data recovery when using infrared cameras for field data monitoring, which leads to high workload and labor costs, and the rigid requirement for mobile communication signal coverage in the monitoring area, which makes maintenance of the monitoring area difficult.

This invention provides an animal behavior correction device, method, and system. The animal behavior correction device is worn on the animal and includes: a positioning module for acquiring the animal's location data and defining the location data of a safe zone; a storage module for acquiring basic animal data; a physiological information acquisition module for acquiring the animal's physiological data; a main control module for determining the location data of the animal and the safe zone, and generating a correction operation and its intensity based at least on the basic data and physiological data when the animal is outside the safe zone; and a correction module for correcting the animal based on the correction operation and intensity to at least bring the animal back to the safe zone. This invention enables animals to perform different correction operations and intensities depending on their condition when leaving an electronic fence, saving on the maintenance costs of physical fences, reducing animal fighting, improving overall animal health, and lowering livestock costs.

The invention provides a medicine abnormal toxicity inspection electronic experiment record management system. The system comprises an inspection method management module, an animal management module, an animal data management module and an inspection result management module. Wherein the inspection method management module can carry out design, auditing and version control on a drug abnormal toxicity inspection experiment recording template; the animal management module is used for recording full life cycle data of experimental animals; the animal data management module is used for recording drug abnormal toxicity inspection experiment data; and the inspection result management module is used for generating, auditing and publishing electronic experiment records of drug abnormal toxicity inspection. According to the embodiment of the invention, the system achieves the automatic and full-life-cycle management of the drug abnormal toxicity inspection experiment data, guarantees the primitiveness, authenticity, safety and traceability of the laboratory data, effectively improves the inspection work efficiency, and achieves the comprehensive, scientific, unified, ordered and efficient computerized system management of the inspection data.

The present disclosure relates generally to keeping animals (10) and in particular to a method for investigating eating behavior of animals (10) in a livestock area (30). The present disclosure also relates to a control device (100) and to a computer program for performing the method. According to a first aspect, the present disclosure relates to a method for investigating eating behavior of animals (10) in a livestock area (30). The method comprises monitoring animal data for a period of time after feed has been dispensed at a feeding station (31) in the livestock area (30), the animal data being collected using tags carried by the animals (10) and being indicative of activity of the animals (10) and / or position of the animals (10) relative to the feeding station (31). The method further comprises performing an action when the monitored animal data fails to meet one or more eating criteria, the one or more eating criteria defining normal eating behavior of the animals (10) in terms of activity of the animals (10) and / or position of the animals (10) relative to the feeding station (31). The present disclosure also relates to a control device (100) and to a computer program for performing the method.

The invention discloses a wild animal on-line monitoring method based on satellite communication, which comprises the following steps: when an infrared sensor detects a signal, a camera module acquires current visual data, and a positioning module acquires spatio-temporal information; the main controller combines the spatio-temporal information and the current visual data into original monitoring data, and performs identification processing on the original monitoring data to obtain optimized data; calculating a transit time window of the next satellite according to the broadcasted satellite ephemeris data; the main controller sends the optimization data to a satellite through a satellite communication module in a transit time window; the satellite sends the optimization data to a ground gateway station; the ground gateway station sends the optimization data to a monitoring center server; the monitoring center server receives and analyzes the optimization data; and the mobile terminal obtains the data. According to the invention, efficient, accurate and intelligent wild animal data monitoring in a public network-free environment is realized. The invention further discloses a system for implementing the method, electronic equipment and a computer readable storage medium.

The application relates to the technical field of animal monitoring, and particularly discloses an experimental animal monitoring system and method, which comprises the following modules: an acquisition module for acquiring basic animal data, monitoring stage data, monitoring stage labels, monitoring target data and animal monitoring data of an experimental animal to be monitored, and determining real-time monitoring data; a monitoring module for determining monitoring abnormal data; an analysis module for acquiring historical abnormal data and determining reason abnormal data of each abnormal reason; an abnormal module for determining a candidate abnormal reason set and an abnormal reason label of each real-time monitoring label of the experimental animal to be monitored; and a determination module for determining real-time animal monitoring data of the experimental animal to be monitored. The candidate reasons and core causes of abnormal animals can be accurately positioned, the integration of abnormal monitoring, reason tracing and real-time data optimization is realized, the monitoring accuracy and systematicness are improved, different monitoring requirements are adapted to, and the real-time animal monitoring data is ensured to be comprehensive and reliable.

The present invention discloses a construction method and system based on the motion of vehicle-mounted virtual human and animal models, which relates to the field of autonomous driving technology, including obtaining autonomous driving scene image information, obtaining human and animal model information based on digitized scene reconstruction according to the autonomous driving scene image information, and obtaining model morphological data based on morphological analysis according to the human and animal model information. The present invention improves target recognition efficiency by selecting human and animal targets, dynamically adjusts the number of nodes required for image recognition through distance adjustment coefficients and node adjustment coefficients, and improves image recognition efficiency while ensuring target recognition accuracy. The human and animal model information provides a data basis for the construction of a human and animal data model, accurately evaluates the motion state of the target through the human and animal data model and the model morphological data, and ensures the stability and reliability of the human and animal model motion construction.

The application discloses a kind of navigation method and system of breeding house inside inspection robot, it is related to intelligent agricultural technology field, the method is by dividing breeding house into several regions, in combination with the shortest path algorithm and depth-first search algorithm, the path of preliminary planning of the inspection robot is patrolled, and environment data and animal data are collected in real time using internal sensor group and intelligent ear tag, by preprocessing, obtain health data group, calculate the health state index of environment and the health state index of animal, further obtain comprehensive health index, and preset first comprehensive health threshold and second comprehensive health threshold are evaluated.In health evaluation triggers path planning, dynamic path optimization model is used to adjust the inspection path, and the area with higher health risk is preferentially covered until the health evaluation of the inspection task area reaches a good state.This method can effectively improve the health monitoring efficiency of breeding environment and animals, and ensure health management and risk control during breeding process.

The invention relates to a quadruped robot traffic inspection controller training method based on animal real data, and the method comprises the steps: collecting animal motion data, solving a pose sequence, obtaining a control strategy through simulation reinforcement learning in combination with an original level state, generating a data set, and building an original level control network output action; and constructing a parameterized complex environment scene, training an environment level control network to output potential vectors to an original level network, and realizing complex environment motion control. According to the method, animal motion data is redirected, and an original level network is constructed by combining simulation reinforcement learning and a variational auto-encoder, so that motion feature representation compression and knowledge multiplexing are realized; environment-level network targeted training is constructed, and the environment-level network and an original-level network cooperatively improve the specific scene control capability; a top layer decision module is introduced to deconstruct an environment into a typical sub-scene, the scene is recognized based on sensing data and an ontology state, a corresponding environment level network is activated, and self-adaptive control is achieved.

The application discloses an ecological corridor guiding device based on biological sensing, which comprises a guiding mechanism, a door sealing mechanism arranged on the guiding mechanism and used for sealing one end of the guiding mechanism, a biological sensing mechanism arranged on the guiding mechanism, an electrical mechanism arranged on the guiding mechanism and used for sending collected wild animal data to an external monitoring terminal for processing and analysis, generating an analysis result, and controlling the door sealing mechanism to open according to the analysis result, and a luring mechanism arranged in the guiding mechanism. The guiding device of the application is arranged at an entrance of an ecological corridor. When the biological sensing mechanism senses that a wild animal meets the condition of entering the ecological corridor, the electrical mechanism drives the door sealing mechanism to open, and the luring mechanism works. The LED lamp group, the ultrasonic wave emitter and the bait luring part in the luring mechanism can lure the wild animal to enter the guiding seat, so that the wild animal can safely enter the ecological corridor, and the wild animal can avoid rejecting and misusing the corridor.

The invention provides a mountain collapse prediction method and a mountain collapse prediction system, and relates to the technical field of mountain collapse prediction. The method comprises the following steps: acquiring animal data of a target mountain area, screening out target resident animals, determining a monitoring site according to a daily activity range of the target resident animals, and performing monitoring. Historical and real-time daily activity video data of target resident animals are collected, behavior features are extracted and compared to obtain distinguishing features, and the distinguishing features are matched to obtain matching scores; when the matching score exceeds a set threshold value, a geological sensor is controlled to collect geological data, if the data is abnormal, it is determined that mountain collapse is about to occur, and early warning information is generated in combination with the distinguishing features. Early warning is realized by utilizing the sensitivity of animals to geological changes, and accurate judgment is performed through geological data.

The application provides a mountain collapse prediction method and a collapse prediction system, and relates to the technical field of mountain collapse prediction. The method comprises the following steps: first, obtaining animal data of a target mountain area, screening out target resident animals, determining monitoring points according to the daily activity range of the target resident animals, and implementing monitoring. Then, collecting historical and real-time daily activity video data of the target resident animals, extracting behavior characteristics, comparing and obtaining distinguishing characteristics, and matching the distinguishing characteristics to obtain a matching score. When the matching score exceeds a set threshold, a geological sensor is controlled to collect geological data. If the data is abnormal, it is determined that a mountain collapse will occur, and warning information is generated in combination with the distinguishing characteristics. Early warning is realized by using the sensitivity of animals to geological changes, and accurate judgment is realized through geological data.

A system for offline-capable, multimodal animal identification and secure data management, consisting of: one or more Internet of Things (IoT) collar devices configured for attachment to livestock. Each device incorporates a variety of physiological sensors and a Bluetooth Low Energy (BLE) communication interface configured to capture and transmit physiological parameters of the livestock via the Bluetooth Low Energy communication interface; a mobile computing device configured to receive multimodal livestock data from one or more IoT collar devices, the captured multimodal livestock data including images of the livestock, images of the muzzle pattern, acoustic vocalization samples, and GPS location data;an artificial intelligence processing module within the mobile computer device, configured to process the multimodal livestock data offline locally, identify breed characteristics of the livestock based on the multimodal livestock data and assess the health status of the livestock based on the multimodal livestock data and physiological parameters, generating a unique livestock identification number (ULID) for each individual animal;a blockchain-based distributed ledger within the mobile device, connected to artificial intelligence processing and configured to store the unique animal identification number, owner information and health data of each individual farm animal, and ensuring tamper-proof verification of the stored information, wherein the blockchain-based distributed ledger enables the creation of a digital twin profile for each individual farm animal, with this digital twin profile being dynamically updated based on incoming multimodal farm animal data and physiological parameters;and an analytics dashboard interface connected to the artificial intelligence module and a blockchain-based distributed ledger, configured to display predictive insights into the health, milk productivity, disease risk, and reproductive cycles of farm animals.

The invention discloses an animal individual information record tagging system and method for a zoo, and belongs to the field of animal data processing. A globally unique ID coding rule and a verification algorithm are adopted to ensure identifier uniqueness and support cross-system data connection; multi-source sensing equipment and a deep learning model are integrated, and automatic feature extraction and high-precision label generation are realized; multi-dimensional correlation analysis and complex retrieval are supported through storage of a hierarchical label system and a graph database; and the data security and the operation traceability are ensured in combination with an authority control and auditing mechanism. According to the scheme, the animal information management efficiency is remarkably improved, individual health monitoring, population optimization management and scientific research decision are supported, and zoo management is promoted to proceed towards the intelligentization and standardization direction.

The application discloses a kind of based on environmental information's plant and animal data intelligent processing method and device, the method comprises: obtaining the environmental information of target area;Receive each data collection point in target area The target data reported by;For each target data, the target data is input into the data classification model of pre-set, and the data classification result of the target data is obtained;According to the data classification result of each target data, all target data belonging to the same data category is determined as a target data category set;Based on the environmental information of target area, the data analysis result of each target data is determined;According to the data analysis result of all target data, the target data analysis result of target area is determined;Wherein, target data analysis result includes the plant and animal survival information of target area. Visible, the efficiency of processing plant and animal data can be improved by implementing the application, and the accuracy of processing plant and animal data can be improved.

A method for generating and distributing simulated animal data includes a step of receiving a set of real animal data at least partially obtained from one or more sensors that receive, store, or send information related to one or more targeted individuals. Simulated animal data is generated from at least a portion of real animal data or one or more derivatives thereof. Finally, the simulated animal data is provided to a computing device. Characteristically, one or more parameters or variables of the one or more targeted individuals can be modified.