93 results about "Flock" patented technology

The invention discloses a shortest-time-based bird flock repelling effect evaluation method for an airport intelligent bird repelling system, and the method comprises the steps: S1, collecting the multi-dimensional monitoring data of an airport bird flock repelling process through a biological feature sensing system, and enabling the multi-dimensional monitoring data to comprise a repelling duration parameter, a region clearing index, and bird flock adaptability response data; s2, based on the multi-dimensional monitoring data, analyzing the spatio-temporal behavior characteristics of the bird flock through an intelligent analysis terminal, and constructing a multi-dimensional bird flock expelling effect characteristic matrix; s3, based on the feature matrix, performing dynamic weight optimization of bird flock expelling effect evaluation indexes with the shortest expelling time as a target, and generating a self-adaptive weight coefficient group; and S4, based on the self-adaptive weight coefficient group, performing panoramic evaluation on the bird flock repelling effect by adopting a time sequence perception memory network, and outputting a repelling efficiency analysis result taking the repelling timeliness as a core. While the flight safety is guaranteed, efficient utilization of bird repelling resources is realized.

The invention provides a laying hen feeding scheme adjustment method and system based on moulting image recognition, and relates to the technical field of intelligent breeding, and the method comprises the steps: obtaining a multi-angle body surface image sequence synchronously collected by a plurality of laying hen individuals in a target chicken flock under a natural light condition; performing semantic segmentation according to the multi-angle body surface image sequence to obtain a feather contour segmentation map set; performing group feature joint extraction according to the feather contour segmentation map set to obtain a multi-dimensional feature tensor representing individual features and group distribution information at the same time; performing group state collaborative inference according to the multi-dimensional feature tensor to obtain a three-dimensional probability distribution vector; performing group nutrition demand mapping according to the three-dimensional probability distribution vector to obtain an optimal nutrition parameter combination suitable for the whole chicken flock; and generating a feeding scheme according to the optimal nutrition parameter combination to obtain a feeding instruction stream. The accuracy and adaptability of nutrition regulation and control in the moulting period are effectively improved.

The invention relates to the technical field of intelligent agriculture and computer vision, in particular to a small-sample high-density chicken counting framework based on a deep learning Mamba structure, which comprises a feature extraction network, a support-query enhancement module and a decoder. According to the method, a multi-scale feature extraction network based on a residual block (ResNet Block) is introduced, so that local detail information is effectively reserved; and then, a support-query enhancement module is constructed by introducing a Mamba structure, and context interaction between support features and query features is effectively enhanced by utilizing the long sequence modeling capability of linear complexity of the support-query enhancement module, so that the problems of individual overlapping and boundary fuzziness in a high-density chicken flock scene are solved. Experimental results on a PoultryCount real breeding data set show that the mean absolute error (MAE) and the root-mean-square error (RMSE) of the method are reduced compared with those of an existing method, and the chicken counting precision and generalization ability under the condition of a small number of labeled samples are remarkably improved.

The invention discloses a small target bird flock motion monitoring system, and belongs to the technical field of bird identification, and the system specifically comprises the steps: obtaining a millimeter wave radar echo signal, a laser radar point cloud data set and a visible light image of a target region; performing spatial clustering segmentation on the laser radar point cloud to generate target point cloud clusters, acquiring a three-dimensional convex hull vertex set for any target point cloud cluster, and mapping a centroid to a millimeter wave radar coordinate system; performing spectrum analysis on the radar echo signals based on the mapping coordinates to obtain Doppler features, and calculating the three-dimensional position of the spatial extremal region in combination with the three-dimensional convex hull vertex set; and mapping the three-dimensional position to a visible light image to generate a spatial constraint mask, extracting an image feature vector and a spatial feature vector, and finally inputting the two types of feature vectors into a classifier model to obtain a bird recognition result, thereby realizing the type recognition of the small target bird flock in a complex scene.

The invention discloses an AI intelligent bird repelling system and method based on multi-modal perception and dynamic deterrence, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining multi-source historical data of birds in an area, extracting bird activity attribute preferences, and generating an initial thermodynamic diagram of long-term activities of the birds; monitoring a bird activity track, a population category and a behavior mode in real time, and dynamically correcting the bird initial thermodynamic diagram to obtain a dynamically updated bird accurate activity distribution diagram; constructing a virtual simulation bird repelling model, obtaining an optimal bird repelling strategy, and generating a dynamic adaptive multi-mode cooperative deterrent instruction set; according to the dynamic self-adaptive multi-mode cooperative deterrent instruction set, a deterrent unit is issued, the deterrent reaction degree is monitored in real time, if it is displayed that the bird flock is effectively repelled, execution is performed according to the current strategy, if it is displayed that the current strategy is invalid or poor in effect, feedback is performed to the virtual simulation bird repelling model, and a new-generation upgrading strategy instruction is generated. The bird repelling device has the advantages that safe repelling of bird flocks is guaranteed, and the influence on the ecological environment is reduced.

The invention provides a heat stress activation state threshold regulation and control method and system based on poultry group behavior feedback, and relates to the technical field of intelligent management and control of livestock and poultry breeding environment, and the method comprises the steps: recognizing the number of poultry heads in a heat wheezing state and the total number of the poultry heads based on poultry head images, and obtaining the real-time heat wheezing proportion of poultry groups; based on a distributed environment real-time acquisition network, obtaining an in-cage environment temperature and humidity index; aiming at each region, integrating data pairs synchronized by a time window, fitting a piecewise linear regression relationship of the real-time heat wheezing proportion of the poultry group along with the change of the temperature and humidity index of the environment in the cage, dynamically generating a heat stress grading threshold value of the region based on a characteristic turning point, generating a house-level regulation and control instruction and a region-level regulation and control instruction, and carrying out region-level regulation and control on the region-level regulation and control instruction. The local environment of the corresponding area is adjusted and alarmed, and a heat stress activation state threshold regulation and control result is obtained. The problems that poultry group heat stress is difficult to accurately and dynamically assess and poultry house environment is difficult to finely and hierarchically control in different production scenes are solved.

The invention belongs to the technical field of computer vision and ecological monitoring, and particularly relates to a large-scale bird flock counting system and method based on pure synthetic data training. In a model training stage, a large-scale bird flock composite image and a pixel-level label thereof are used as a unique training set, and end-to-end training is performed on a point prediction deep learning counting network using VGG19-BN as a backbone network to obtain a trained bird flock counting model; in the model training stage, real world bird flock images to be counted are input into the trained bird flock counting model, the model directly outputs predicted bird individual position points, a final counting result of the bird flock is obtained by counting the number of prediction points with high confidence, and a bird flock density distribution diagram can be generated for visualization. The invention provides a method and a system for realizing real scene high-precision counting only through synthetic data training based on a point prediction network aiming at the technical problems of strong dependence of real labeled data and insufficient cross-domain generalization ability of a model in a bird flock counting task.

The invention provides a Tibetan chicken intensive breeding health monitoring and early warning method and system, and relates to the technical field of computers, and the method comprises the steps: obtaining the three-dimensional motion and interval time sequence data of a Tibetan chicken flock in a breeding house, and the original chirp audio time sequence data; performing motion mode analysis according to the three-dimensional motion and the interval time sequence data to obtain a vector field sequence; carrying out stress level inference according to the vector field sequence to obtain a group recessive stress index; according to the group implicit stress index and the original chirp audio time sequence data, performing model construction to obtain a chirp-stress association model; acquiring real-time chirp audio data, and inputting the real-time chirp audio data into the chirp-stress correlation model for health state critical point prediction to obtain an instability precursor signal; and performing graded early warning according to the instability precursor signal to obtain a health early warning grade. According to the invention, prediction and early warning of health risks caused by group stress of the Tibetan chickens in an intensive breeding environment are realized.

The invention relates to the technical field of laying hen breeding, and discloses a laying hen breeding accurate feeding adjusting system based on big data cloud-side collaboration. The system comprises an environmental data acquisition module, a cloud edge collaborative analysis module, a multi-dimensional difference evaluation module, an abnormal area positioning module, a feeding strategy adjustment module and an encryption communication link module. The environment data acquisition module acquires chicken flock multi-source data streams through various sensors, and standard chicken flock data is generated after processing; a cloud-edge collaborative analysis module constructs a dynamic feed supply model according to the dynamic feed supply model and outputs theoretical feed demand; the multi-dimensional difference evaluation module performs multi-dimensional comparison on the theoretical value and the actual consumption value to generate a feed difference coefficient matrix; the abnormal area positioning module generates an abnormal feeding probability distribution diagram in combination with farm topological information; the feeding strategy adjusting module generates a self-adaptive feeding control signal based on the graph; the encryption communication link module transmits a control signal to an actuator through a quantum encryption channel. The system realizes accurate adjustment and safety control of feeding for laying hen breeding.

The invention discloses a bird flock oriented repelling path planning method based on a Maklink intelligent airport bird repelling system, and the method comprises the steps: S1, recognizing the surrounding environment of an airport through a radar and photoelectric equipment, carrying out the environment modeling based on a Maklink link diagram theory, and generating a two-dimensional environment model; s2, based on the two-dimensional environment model, planning a repelling path of the airport intelligent bird repelling system by adopting an APF-RRT algorithm, determining path points of bird flock flight, and generating a bird repelling path set; and S3, optimizing the bird repelling path set based on a preset probability function, increasing the probability that the path passes through the safe target area, and generating a guidance repelling path. The guidance bird repelling effect is achieved, it is ensured that the bird flock leaves the airport area according to the expected direction, and therefore the success rate and safety of bird repelling are improved.

The invention relates to the technical field of ecological monitoring and computer vision, and particularly discloses a large-scale bird flock automatic labeling synthetic data generation method and system. The technical problem to be solved is to overcome the defects that in the prior art, the acquisition cost of large-scale bird flock counting task annotation data is high, the quality is difficult to guarantee, and the authenticity and scale of synthetic data are limited. According to the technical scheme, the method comprises the following steps: based on acquired real small-scale bird flock three-dimensional trajectory data, performing group scale expansion by using a collective motion model such as an inertial spin model, and generating a large-scale bird flock three-dimensional motion trajectory; a pre-established three-dimensional bird model and a flight animation are endowed with the motion trail, rendering is performed in a virtual rendering engine, and an initial synthetic image and a corresponding pixel-level precise labeling mask including a binary mask of the whole bird flock and an instance segmentation mask of each individual are generated; and performing visual reality enhancement processing on the initial synthetic image, migrating the real bird texture to the synthetic bird through style migration, and fusing the mask and the real background image to generate a final synthetic image with high reality, and strictly maintaining the integrity of the annotated mask at the same time. The method is mainly used for automatically generating precisely labeled and highly realistic large-scale bird flock images, provides efficient data support for bird flock automatic counting model training, and can be applied to ecological monitoring and protection.

This invention relates to the field of migratory bird distribution detection technology, specifically disclosing a method for detecting migratory bird distribution in wetland protected areas based on image sensors, including the following steps: Step S1: Divide the protected area into several sub-regions, set up image acquisition points in each sub-region, acquire migratory bird images in real time, identify the instantaneous number of migratory birds in the images, and simultaneously record the acquisition timestamp and acquisition coordinates; Step S2: Construct a spatiotemporal counting matrix based on the number of migratory birds at different times at each acquisition point, with acquisition coordinates as rows and time as columns, and obtain several basic spatiotemporal patterns and the corresponding linear weights of each pattern through matrix decomposition; Step S3: Based on the change of the linear weights of each basic spatiotemporal pattern over time, identify the migration events of migratory bird flocks between sub-regions, combine the migration events with the spatial distribution preference vectors of each pattern, determine the migratory bird flock gathering areas and migration channels, and generate the final distribution detection results.

This invention discloses a method and system for analyzing the health status behavior of poultry flocks from images, relating to the fields of computer vision and smart farming technology. The method includes: firstly, acquiring monitoring images and extracting the poultry's location coordinates; secondly, dividing the poultry into an active first target set and an inactive second target set based on displacement features; thirdly, constructing a discrete topological network using the first target set to generate candidate spatial gap regions and identifying edge targets; fourthly, generating a biological rejection intensity index based on the head orientation vector of the edge targets, and determining stable rejection regions based on temporal stability; and fifthly, outputting a health anomaly warning when the center of the stable rejection region and the coordinates of the second target set satisfy spatial matching conditions. This invention effectively solves the problem of distinguishing between physiological quiescence and pathological stagnation in high-density farming by analyzing the group's biological rejection behavior to pinpoint abnormal individuals, thus improving monitoring accuracy.

The invention discloses a breeding method of high-yield laying hens, and belongs to the technical field of chicken breeding. The method comprises the following steps: S1, environment monitoring and comfort calculation; s2, individual feeding amount calculation and feeding; s3, chicken flock behavior monitoring and welfare optimization; s4, regulating and controlling flavor and taste; s5, health and safety monitoring; s6, performing digital twin closed-loop optimization; and S7, carrying out actual breeding according to a breeding strategy generated by the digital twin system. According to the method, the environment, feeding, behaviors, welfare, flavor and health are dynamically predicted and regulated through the digital twin chicken flock model, closed-loop optimization of the whole breeding process is achieved, the chicken flock is always in the physiological and environmental state close to the optimal state, and therefore the laying rate is remarkably increased, and the breeding cost is reduced. The phenomenon of egg laying reduction caused by environmental fluctuation, insufficient nutrition or stress reaction is reduced.

The application discloses an intelligent inspection management system and method for large-scale chicken breeding, and relates to the technical field of breeding management. In the process of artificial one-by-one inspection of chicken flocks, the inspection results of each type are recorded, and the high-spectrum image of the tail feather of the chicken and the call recording of the chicken are synchronously collected; the high-spectrum image features of the tail feather of the chicken and the audio features of the call recording of the chicken under the inspection results of each type are classified and extracted; the correlation calculation is performed, and the high-spectrum image feature range of the tail feather and the audio feature range of the call recording corresponding to the inspection results of each type are classified; the high-spectrum image of the tail feather and the call recording of the chicken in the breeding farm are batch-collected and the features are extracted, the high-spectrum image feature range of the tail feather and the audio feature range of the call recording corresponding to the inspection results of each type are compared, and the inspection results of the chicken are batch-obtained. The application realizes batch intelligent detection management of the chicken for large-scale breeding.

The invention discloses electric driving type fluff extraction equipment, which belongs to the technical field of wormwood processing, and comprises a machine body assembly, a fluff extraction device, a fluff extraction device and a control device, the electric driving assembly is assembled on the machine body assembly and provides electric driving force; the electric driving assembly comprises a rotary driving assembly, a power driving assembly and a lifting assembly, the rotary driving assembly and the power driving assembly are assembled on the machine body assembly, and the power driving assembly is partially assembled on the rotary driving assembly and drives the rotary driving assembly to rotate; the lifting assembly is driven to lift back and forth; the down lifting assembly is assembled on the machine body assembly, and the lifting assembly is assembled on the down lifting assembly and drives the down lifting assembly to lift down in a reciprocating mode; compared with the prior art, the flock extraction speed of the flock extraction head is uniform, and the flock extraction quality of folium artemisiae argyi can be improved.

This invention discloses a method, apparatus, equipment, and storage medium for the synergistic blocking of harmful substances in chicken houses. The method includes collecting environmental parameters, physiological states of the flock, and pathogen information from the chicken house; sending the collected information to an intelligent decision-making system; and when parameters exceed thresholds or pathogenic agents are detected, the intelligent decision-making system generates a synergistic control strategy and triggers a coordinated response: a light disinfection system activates a specific wavelength light source to form an effective disinfection area; a ventilation system guides airflow into the effective disinfection area; a drinking water disinfection system adds effective disinfectants and immune enhancers to the drinking water; and the intelligent decision-making system dynamically adjusts the parameters. In this embodiment, the light disinfection system, ventilation system, and drinking water disinfection system not only achieve the effect of a single disinfection method, but also work together to significantly reduce the risk of highly contagious diseases in the flock, ensuring the normal growth of the chickens and avoiding economic losses caused by diseases.

The application discloses a laser radar airport bird group detection and early warning method and system based on a DGNN, relates to the technical field of airport operation safety monitoring, and comprises the following steps: collecting continuous three-dimensional point cloud data of an airport runway, a taxiway and adjacent airspace by using a laser radar device and performing preprocessing to form a continuous multi-frame structured point cloud sequence; taking points or point cloud clusters in the sequence that meet preset space and intensity conditions as graph nodes, establishing a connection edge between the nodes according to a spatial proximity relationship between the nodes, a time continuity relationship and operation similarity, and forming a dynamic graph structure that evolves over time; jointly analyzing the features of the graph nodes and the mutual relationship thereof by using a DGNN, and identifying bird targets in the nodes; aggregating the identified bird targets to construct a bird group cluster set, combining a bird strike risk assessment model, calculating a potential risk value of the bird group cluster to the operation of the airport, and performing graded early warning according to the risk value, so that integrated bird group detection, behavior analysis and risk early warning are realized.

The invention provides an illumination system arranged to illuminate a space for rearing a flock of birds, wherein the illumination system comprises: a visible light source configured to emit visible light; an ultraviolet light source configured to emit ultraviolet light; a controller configured to: (i) entrain a circadian rhythm of the flock of birds by controlling the visible light source to emit the visible light for a predetermined period of light, and not to emit the visible light for a predetermined period of dark; (ii) control the ultraviolet light source to emit the ultraviolet light at an ultraviolet light intensity for at least one subperiod within the predetermined period of dark, wherein the ultraviolet light comprises a peak wavelength within the UV-A wavelength range.

The utility model is suitable for the technical field of poultry breeding, and provides a large-scale raw chicken breeding henhouse with a temperature control function, which comprises a henhouse main body, the temperature control part is arranged on the inner side wall of the henhouse main body; the breeding mechanisms are arranged in the henhouse main body; each group of breeding mechanism comprises two breeding cages which are stacked up and down; an adjusting mechanism is arranged at the position, arranged on the upper portion of the breeding cage, of the henhouse body, and the adjusting mechanism is electrically connected with the temperature control part; the temperature and the humidity in the chicken house are monitored in real time and accurately regulated and controlled, the filter box is adopted for air purification, an optimal and healthy growth environment is created for chicken flocks, the growth efficiency of the chicken flocks is remarkably improved, the disease risk is reduced, and through efficient breeding mechanism design and humanized management measures, the breeding cost is reduced, and the breeding efficiency is improved. The breeding efficiency is greatly improved, and the cleanliness and sanitation of the breeding environment are kept, so that the healthy growth of chicken flocks is promoted, and the risks of disease transmission and environmental pollution are reduced.

The invention discloses a feed delivery line self-adaptive accurate feeding method, and belongs to the technical field of feeding, and the method comprises the steps: collecting chickens and chicken flocks to obtain multi-modal data and chicken behavior data; constructing a social network graph of the chicken flocks according to the chicken behavior data to obtain individual indexes of each chicken, obtaining fusion data based on the multi-modal data, the chicken behavior data and the individual indexes, inputting the fusion data into a multi-modal time sequence prediction model to obtain growth trend prediction data of each chicken, and predicting the growth trend of each chicken according to the growth trend prediction data. A composite feeding strategy is obtained based on the growth trend prediction data and the feed consumption, and the feed conveying line unit is regulated and controlled to conduct feeding according to the composite feeding strategy. According to the method, the dynamic nutritional requirements of chicken flocks in different growth stages, different environment temperatures and different health states can be met, the individual difference between different chickens is met by predicting the growth of each chicken, the laying rate of the chickens is increased, and the feeding amount of feed can be adaptively adjusted according to a composite feeding strategy.

The utility model provides an anti-bird thorn, which belongs to the technical field of bird repelling, and comprises a support rod, an anti-bird assembly and a fixing assembly, the anti-bird assembly comprises auxiliary rods arranged on two sides of a connecting ring, the outer wall of each auxiliary rod is movably connected with a plurality of support rings, and one side of each support ring is spliced with an auxiliary ring; the beneficial effects of the utility model are that through the arrangement of the anti-bird thorns, when birds want to nest and stay on electric power facilities, when the birds step on the anti-bird thorns, the anti-bird thorns rotate through the support ring and the auxiliary ring under the gravity of the birds, the birds are prevented from standing on the anti-bird thorns and then nesting, and through the utilization of the reflective tape, dynamic reflective points can be generated when sunlight irradiates, so that the anti-bird effect is improved. When the bird repelling device is used, a user can take down the fixing cap from the auxiliary rod, take down the supporting ring and the auxiliary ring and replace the supporting ring and the auxiliary ring with larger bird repelling thorns according to bird flocks inhabiting in places so as to deal with the bird flocks, and therefore the purpose of bird repelling is achieved.

The present application belongs to the technical field of runway airspace bird situation monitoring, and particularly relates to an ultrasonic array direction finding runway airspace bird situation monitoring and bird repelling triggering method, which comprises the following steps: arranging ultrasonic array direction finding units on both sides of the runway through joint calibration, collecting multiple array echoes to construct a data set with time stamps, obtaining the three-dimensional position of the bird flock based on the joint estimation of the time difference of arrival and the angle of arrival, and generating a bird flock trajectory sequence, projecting the trajectory into a three-dimensional airspace grid model with the runway centerline as the reference, calculating the grid risk index according to the closest distance of the bird flock to the runway centerline and the relative speed, selecting a high-risk grid to generate a bird repelling triggering control instruction set, driving the corresponding array to perform directional ultrasonic bird repelling, and correcting the bird flock trajectory and the triggering grid based on the updated echo data after bird repelling, thereby solving the problems of three-dimensional direction finding accuracy and bird repelling triggering area for long-distance and high-uncertainty bird flocks.

The environment detection unmanned ship comprises an unmanned ship body, a supporting frame is fixedly connected to the middle of the unmanned ship body, a positioning frame is fixedly connected to one end of the top of the supporting frame, a water quality detection assembly is assembled on the inner side of the positioning frame, and a wind speed sensor is fixedly connected to the middle of the top end of the supporting frame; the multiple positioning plates are fixedly connected to the two sides of the top of the supporting frame respectively, and the ends, away from the supporting frame, of the positioning plates are fixedly connected with bird repelling covers; the knocking assembly is assembled between the positioning plate and the bird repelling cover and used for being matched with the bird repelling cover to make a sound to repel bird flocks. Through the structural cooperation of the bird repelling cover and the knocking assembly, when the unmanned ship body is parked, airflow can be captured and sound can be made, so that birds at the unmanned ship body are repelled, and the situation that the detection precision of the sensor of the unmanned ship body is affected by the existence of the birds is avoided.

The utility model relates to a door body assembly which is used for opening or closing a putting opening of a clothes processing device and comprises a door plate, a clothes processing cavity, a door cover and a door body, the door shell faces the clothes processing cavity; the door plate and the door shell are in butt joint, and a door body cavity is formed between the door plate and the door shell. The flock collecting box is used for filtering and collecting flock, and the air inlet end of the flock collecting box is communicated with the clothes processing cavity; the flock removal fan assembly is arranged in the door body cavity and comprises a flock removal fan used for providing suction force, and the flock removal fan is communicated with the air outlet end of the flock collection box so as to form a flock removal air path sequentially passing through the flock collection box and the flock removal fan. The flock removal fan assembly is arranged in the door body cavity, so that the flock removal air path independent of the drying air path is formed in the inner space of the door body, the flock removal capacity is improved under the condition that the clothes drying efficiency is not affected, and the flock manual cleaning frequency is reduced.

The invention discloses an ecological breeding henhouse, and relates to the technical field of ecological breeding, the ecological breeding henhouse comprises a henhouse body, a power supply, a photovoltaic panel and a control assembly, the front side of the henhouse body is provided with a fixed frame, a diamond net is laid on the fixed frame, a hinge frame is rotatably connected to the fixed frame, and two sides of the hinge frame are provided with locking holes; a sliding block is arranged at the output end of the electric telescopic rod. A sliding hole is formed in the wall of the cavity, a locking block is slidably connected into the sliding hole, the locking block is sleeved with a reset spring, the reset spring abuts against the position between the end of the locking block and the inner wall of the cavity, the photovoltaic panel is connected with the power source, and the power source is electrically connected with the electric telescopic rod through the control assembly. The diamond net laid on the fixing frame can effectively resist invasion of natural enemies such as yellow weaves and mice, chicken flocks are prevented from being disturbed or hurt by the outside, and the breeding safety is greatly improved; the diamond net can guarantee air circulation and can achieve closed protection by closing the hinged frame when needed, and the problem that ventilation and safety of a traditional henhouse are difficult to achieve at the same time is solved.

The present application relates to the technical field of image data processing and object positioning and identification, in particular to a method for identifying and analyzing the geographic position of bird flocks by high-definition cameras, comprising: deploying multiple high-definition cameras, collecting video streams in real time and synchronously recording the spatial position parameters and attitude parameters of each camera itself; using an improved YOLOv8 model to detect bird targets in the video; the improvement includes introducing P2 layer feature maps from Backbone and adding corresponding P2 detection heads in the detection head, while removing the P5 detection head. By improving the YOLOv8 model, the present application introduces the P2 detection head to enhance the small target recognition capability, and fuses the observation angles of multiple cameras, uses spatial geometric solution and dynamic clustering technology, and finally outputs the accurate three-dimensional coordinates of the bird flock in the real world. While significantly improving the positioning accuracy and recognition rate, the present application has the advantages of strong system robustness, low deployment cost and easy expansion.

The present application belongs to the technical field of wetland bird detection, and particularly relates to a wide-area bird flock detection and counting method based on multi-dimensional information fusion. The method comprises the following steps: S1: mounting visible cameras, infrared cameras and polarization cameras with the same field of view on an unmanned aerial vehicle to perform multi-dimensional image acquisition; S2: using the multi-dimensional image acquisition results obtained in step S1 to prepare a flying bird detection data set; S3: constructing a flying bird detection deep neural network, training the flying bird detection deep neural network using the flying bird detection data set, and obtaining a trained flying bird detection deep neural network; S4: performing multi-dimensional image acquisition on flying birds in a to-be-detected area, and inputting the multi-dimensional image acquisition results into the trained flying bird detection deep neural network to perform flying bird type detection and flying bird pixel position detection; and S5: counting the types and quantities of flying birds in the to-be-detected area according to the detection results of step S4. The present application has the advantages of automation, high precision and rapidity.

The invention relates to a wind-light-electricity three-power-supply AI intelligent identification bird repelling device, and belongs to the technical field of electric power safety and intelligent operation and maintenance. According to the device, the coaxial multispectral imaging module, the 360-degree high-definition camera and the voiceprint recognition sensor array are fused, so that all-weather and multi-mode recognition of birds is realized. The system adopts triple power supply of solar energy, commercial power and wind energy, is equipped with intelligent load prediction and temperature self-adaptive charging control, and realizes energy optimization management. Through bird flock density dynamic evaluation and graded bird repelling response, bird repelling accuracy and intelligence are improved. The system improves the recognition rate and the power supply reliability in a complex environment, and is suitable for the field of bird damage protection of electric power facilities.

This invention relates to the field of bird strike prevention and control technology, specifically to a method and system for timely early warning and prevention of bird flocks at airports based on radar monitoring. It utilizes radar to scan a monitoring area in real time, obtaining real-time dynamic data on bird activity, integrating this data into a monitoring dataset, generating spatial mapping data reflecting the spatial density distribution and gathering hotspots of bird flocks within the monitoring area, and defining risk zones. If, based on the real-time dynamic data, it is determined that a bird flock has entered a risk zone, dynamic adjustment parameters are generated to optimize the scanning strategy of the radar monitoring system. A real-time updated monitoring report is generated based on the real-time dynamic data, further generating a prevention and control command dataset and a final response plan. The technical solution presented in this invention, based on radar monitoring of the target area, provides accurate data with a wide coverage area. Furthermore, by adjusting the radar scanning strategy after a bird flock enters a risk zone, it improves data monitoring accuracy, resulting in highly accurate and timely monitoring reports.