104results about How to "Understand in time" patented technology

The invention discloses an intelligent henhouse environment concentration monitoring system, and relates to the technical field of henhouse environment concentration monitoring. The influence of changes of environmental parameters in a henhouse in different seasons on chicken raising is solved. The system specifically comprises a sensor module, a data acquisition module, a data transmission module, a data processing module and a remote monitoring module, the sensor module acquires various environmental parameters in a henhouse and transmits the acquired data to the data acquisition module, and the data acquisition module receives the data transmitted by the sensor module, pre-processes the data and transmits the pre-processed data to the remote monitoring module. The preprocessed data is uploaded to the data processing module through the data transmission module, the data processing module analyzes and processes the data, and the collected original data is converted into useful information understood by a breeder. Parameters of the model can be obtained by fitting the model into historical data, and the parameters are used for predicting the influence of changes of environmental parameters in the henhouse on chicken raising in different seasons in the future.

The invention relates to an intelligent question-answering system and question-answering method for tobacco industry professional knowledge based on a big language, and the system comprises a training data collection unit which is used for collecting related professional knowledge and related work flow and system files of the tobacco industry, and carrying out the deep learning and training, and forming a knowledge base; the model construction unit is used for constructing a large language model platform; the user interaction unit is used for performing information interaction between employees and the constructed large language model platform; the text question and answer unit is provided with an answer text acquisition module, a question generation module and a preset dialogue generation model; the knowledge base access module is used for accessing the employee question and answer text as a knowledge base to the large language model platform through a preset dialogue generation model; and the matching answer output module is used for searching answers matched with the questions from the knowledge base and outputting the matched answers. Through combination with an existing business process, a large language model privatization deployment platform is constructed, internal enterprise WeChat is connected, and intelligent question answering and pushing are formed.

The invention belongs to the technical field of dynamic traffic, and particularly discloses a multi-source data fusion traffic dynamic induction method, which comprises the following steps: S1, traffic information is acquired from multi-source heterogeneous data, and the data comprises real-time traffic information, navigation map data, a road network topological structure and a public traffic timetable; s2, carrying out data fusion processing on the traffic information obtained in the step S1, and generating fused traffic state estimation; s3, on the basis of travel historical records and preferences of the user, constructing a personalized travel guide model, and providing an optimal travel suggestion; and S4, monitoring the traffic condition in real time, performing dynamic adjustment based on user feedback and emergencies, and optimizing the travel path. By integrating real-time information from various data sources, comprehensive perception of road traffic conditions is ensured, traffic changes in space and time can be processed at the same time, the weight is dynamically adjusted according to the reliability of the data sources, and the influence of data islands and information loss is reduced.

The invention discloses a remote monitoring robot for health monitoring of old people, and relates to the technical field of monitoring robots, the remote monitoring robot comprises a mobile robot module, and the mobile robot module is in communication connection with a deep learning algorithm module, a voice module, an anomaly detection module, a positioning module and an emergency safety guarantee module. According to the remote monitoring robot for health monitoring of the old people, by integrating a deep learning algorithm and a mobile robot technology, a safe living space is provided for the old people, activities of the old people are monitored in real time, and it is ensured that the old people can be timely helped when encountering health crisis through a fall-down detection and emergency situation feedback mechanism; when it is detected that the old man falls down through a YOLOv5 algorithm, help seeking information is immediately sent to a preset guardian, in addition, the mobile following function of the robot provides continuous monitoring when the old man goes out, and the robot can closely follow the old man at home or outdoors to ensure that no dead angle exists in monitoring.

The invention discloses an infectious disease intelligent monitoring and early warning processing system and method, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting multi-source data in real time, and carrying out the preprocessing; key features are extracted from the preprocessed data through a feature engineering technology, and a data set is formed; initializing an early warning model and training the early warning model, and dynamically adjusting parameters of the early warning model by adopting a self-adaptive adjustment mechanism to obtain an optimized early warning model; performing real-time analysis by using the optimized early warning model, and evaluating the risk that the individual is infected with the specific infectious disease; and providing personalized prevention suggestions according to an individual risk assessment result. According to the method, multi-source data is collected in real time and refined, a high-quality data set is constructed in combination with a feature engineering technology, and the optimized early warning model is used for real-time risk assessment, so that generation of individualized prevention suggestions is realized, potential high-risk individuals can be recognized earlier, targeted prevention measures are provided, and the risk assessment efficiency is improved. Therefore, transmission of infectious diseases is effectively controlled.

The invention provides a mobile communication terminal detection method and device, and relates to the technical field of communication detection, and the method specifically comprises the steps: collecting transmission information and environment information, carrying out the data analysis, and generating a transmission index and an environment influence index; performing correlation analysis on the transmission index and the environmental influence index to generate a communication quality index of the mobile communication terminal, and comparing the communication quality index with a preset quality index threshold to obtain a detection result; according to the invention, multiple items of information of the mobile communication terminal are collected through the system, comprehensive analysis is carried out in combination with transmission information and environment information, and a more comprehensive and accurate communication quality assessment method is provided. By generating the transmission index and the environmental influence index and combining dimensionless processing and correlation analysis, the communication quality index can be scientifically evaluated, and the problem that multiple factors cannot be comprehensively considered in the traditional technology is effectively solved.

The invention provides a train delay time prediction method and device, equipment and a medium. The method comprises the steps that a delay feature data set based on cause events and a train operation data set based on a working diagram are constructed; performing feature engineering processing on the preprocessed late feature data set to obtain a first feature data set; a train delay time prediction model is constructed, a convolutional neural network is trained with the first feature data set as input and the delay train delay time as output, and the output of the convolutional neural network, the planned running diagram parameters and the actual running diagram parameters as input; the late time of each station after the late train arrives at the S station is used as output to train the long short term memory network; and receiving train delay information and running diagram information of the fault train, inputting the train delay information and the running diagram information into the convolutional neural network to obtain delay time, and predicting and determining the delay time of the fault train arriving at each station after the S station by combining the running diagram information long-short memory network.

The invention belongs to the technical field of biological detection, and particularly relates to an auxiliary device for bovine tuberculosis kit detection and a use method of the auxiliary device. The problems that existing bovine tuberculosis detection equipment is large in size, inconvenient to carry to the site, complex in operation, low in detection efficiency and high in detection cost are solved. According to the scheme, a plurality of vibration assemblies are arranged on a box body, the vibration assemblies are connected with a supporting assembly, the vibration assemblies are used for driving the supporting assembly to move up and down, a storage box is placed on the supporting assembly, a pore plate is arranged on the storage box, and a sample tube is placed on the pore plate; the auxiliary device for bovine tuberculosis kit detection has the advantages of being small in size, light in weight, easy and convenient to operate, convenient to carry, low in cost and the like so as to meet the requirement for on-site rapid detection, especially in areas with limited resources, the timeliness and accuracy of bovine tuberculosis diagnosis are improved, prevention and control measures can be taken in time, and the detection efficiency is improved. Disease transmission risks are reduced, and healthy development of animal husbandry is guaranteed.

The invention discloses a portable rehabilitation training and intelligent evaluation system, and relates to the technical field of computer-aided diagnosis. The portable rehabilitation training and intelligent evaluation system is mainly composed of wearable motion sensing equipment, a wireless receiver, a portable suitcase, a network communication module and rehabilitation training and intelligent rehabilitation evaluation software. The system has rehabilitation training, rehabilitation evaluation and remote rehabilitation cloud platform interaction functions. According to a patient rehabilitation evaluation result and clinical data, an individualized rehabilitation prescription model is established, a patient individualized rehabilitation prescription is generated, multi-source feature fusion is carried out through a feature fusion formula provided by the invention, a virtual reality scene interactive game is controlled by fused features, and individualized and targeted rehabilitation training is carried out; an artificial intelligence quantitative evaluation model is established through deep learning, a nonlinear dynamic tool is designed to visualize an evaluation result, and a quantitative evaluation result consistent with a clinical Fugl-Meyer scale and an intelligent staging result consistent with a Brunnstrom staging are realized.

The present invention provides a flood warning detection method and system based on a GCN graph convolutional neural network, the method comprising: S1, deploying multiple data acquisition devices in a target area; the data acquisition devices include online monitoring devices for real-time acquisition of original water flow data at the monitoring location; S2, preprocessing the original water flow data and processing outliers to obtain processed water flow data; S3, converting the processed water flow data into a vector form suitable for input into a neural network, and constructing a graph structure of the water flow data; S4, constructing a graph convolutional neural network architecture, training and optimizing the network; using an adaptive algorithm to dynamically adjust model parameters, and an output layer generates flood warning results; S5, training historical water flow data and real-time water flow data, and constructing a flood warning detection model; S6, using the flood warning detection model to perform flood warning prediction, and outputting the obtained real-time flood warning information to a user interface; the method can provide more accurate and reliable prediction results for flood warning.

The invention discloses a perovskite photovoltaic module defect detection method and device and a storage medium, and belongs to the field of perovskite photovoltaics. The method comprises the following steps: irradiating the back surface of a to-be-detected perovskite photovoltaic module, performing first image acquisition on a perovskite layer in the to-be-detected perovskite photovoltaic module to obtain a first image, and determining defect position information and film thickness information in the first image based on the first image; performing second image acquisition on the position of the defect based on the position information of the defect to obtain a second image; based on the second image, judging the types of the defects, and counting the types of the defects to obtain the number of each type of defects; and judging whether the to-be-detected perovskite photovoltaic module is qualified or not based on the number of various types of defects or the film thickness information of the first image. According to the invention, the defects of the to-be-detected perovskite photovoltaic module can be rapidly detected, analyzed, judged and early warned, so that the yield of products can be improved.

The invention relates to an interface display method and device, electronic equipment and a storage medium. The interface display method comprises the steps of obtaining state information of a first account in response to dialogue operation executed for the first account, and displaying a first dialogue interface with the first account; wherein when the state information meets a preset condition, the first dialogue interface displays a dialogue switching entrance; and in response to a trigger operation for the dialogue switching entry, displaying a second dialogue interface with a second account, at least one target published content published by the first account including a target recommended content related to the second account. By adopting the method, the browsing object can know the related information of the article in time, meanwhile, the consultation amount and the browsing amount of the related article of an enterprise are increased, and the timeliness of information transmission is improved.

The invention relates to a circuit board backdrill capacitance testing method, device and equipment and a storage medium, and the method comprises the steps: obtaining a capacitance detection instruction, and obtaining the image information of a to-be-detected circuit board according to the capacitance detection instruction; carrying out clustering analysis on the image information of the to-be-detected circuit board by adopting a k-means algorithm to obtain a feature image of the to-be-detected circuit board, and carrying out analysis according to the feature image to obtain a displacement distance and an angle of the probe; adjusting the position of the probe according to the displacement distance and the angle of the probe, and generating a capacitance measurement message after the adjustment of the probe is completed; according to the capacitance measurement message, calculating a capacitance value of the circuit board to be detected through a capacitance method, and comparing the capacitance value of the circuit board to be detected with a preset capacitance value to obtain a capacitance comparison result; and generating a quality evaluation result of the back drilling hole of the circuit board according to the capacitance comparison result, and transmitting the quality evaluation result of the back drilling hole of the circuit board to the user side. The method has the effect of improving the precision and efficiency of back drilling hole quality detection.

The invention discloses an electrical fire identification and early warning system and method, which can be applied to the technical field of fire early warning. According to the application, a deployment mode of end-side cloud is realized through a plurality of slave ends, a host end and a data background, so that mass data can be monitored and pre-warned, and meanwhile, a temperature sensor, a current sensor, a controller and a wireless transmission module are arranged in each slave end; real-time current and real-time temperature of a monitored cable can be collected and transmitted through the slave end, and a controller, a temperature sensor and a wireless transmission module are arranged in the host end, so that the ambient temperature of the position where the monitored cable is located can be collected through the host end. And the second real-time current and the second real-time temperature are combined to carry out electrical fire identification early warning operation, so that the real-time performance and accuracy of electrical fire identification early warning can be effectively improved, alarm reminding is carried out in a data background, and a worker can know the state of the cable in time.

The utility model is suitable for the field of beauty instruments, and provides a storage box and a beauty instrument assembly. According to the storage box provided by the utility model, the box body vertically placed on the carrying table is arranged, the storage position for storing the beauty instrument is arranged in the box body, the display control screen is arranged on the box body, and the display control screen is configured to be vertically arranged when the box body is vertically placed on the carrying table so as to be arranged towards a user. According to the storage box provided by the embodiment of the utility model, the display control screen is configured to be vertically arranged and arranged towards the user, so that when the user uses the beauty instrument, the user can conveniently observe the content displayed on the display control screen, the user can timely know the current function mode, state and other information of the beauty instrument and the storage box, and the user experience is improved. And the user experience is improved.

The invention discloses a real-time intelligent disaster early warning method based on multi-modal data, and belongs to the technical field of disaster early warning, and the method comprises the steps: 1, constructing a multi-modal data platform; 2, obtaining a first training model by using a graph neural network technology, and obtaining a second training model in combination with a federated learning technology; 3, integrating the first training model and the second training model to obtain a disaster propagation model; 4, deploying a response function on edge equipment close to the data source; and 5, continuously collecting data of actual disaster occurrence, comparing the data with a model prediction result, and carrying out early warning response. According to the invention, by integrating disaster data obtained by a plurality of data sources, more data sources can be obtained, the comprehensiveness and accuracy of early warning can be improved, and the generalization ability of the model can be significantly improved by constructing the disaster recognition model by using the graph neural network and federated learning, so that the system can cope with various complex and changeable disaster scenes.

The invention discloses an early warning method and device for activity abnormity of home-based care personnel, and relates to the technical field, the method comprises data acquisition, data analysis, an early warning mechanism and subsequent processing.Through multi-dimensional combination of a motion sensor, an intelligent bracelet and a camera, activity data of old people are comprehensively acquired from different angles, the activity state of the old people is reflected in real time, and the early warning effect is good. According to the invention, family members and nursing personnel can timely know the situation and rapidly respond when abnormity occurs, the safety is improved, the design of the smart bracelet is very intimate, an elderly activity abnormity algorithm is established, the elderly activity modes are divided into very active, general active and inactive, the activity rules are analyzed for different groups, and the elderly activity abnormity algorithm is established. Activity data of the elderly are compared with a group mode to which the elderly belongs in real time, abnormity can be found in time, mild, moderate and severe abnormity indexes are set in an early warning mechanism, accurate response is performed according to the severity of abnormal conditions, and the survival probability of the elderly in home life is integrally improved through the combination of the method and the device.

The present invention relates to the technical field of quality tracing, specifically to a quality tracing management system and method for the entire production process of aluminum profiles, including a data comparison unit, a data query unit and a quality tracing unit, and also including: a node definition unit, the node definition unit is used to perform node definition on the entire production process of aluminum profiles to obtain a production node set for the entire production process of the aluminum profiles, the production node set includes a raw material procurement node, a smelting workshop node, an extrusion molding workshop node, a heat treatment workshop node, a surface treatment workshop node, a quality inspection node and a transportation node, and the production node set of the entire production process of the aluminum profiles is transmitted to a blockchain construction unit and a real-time monitoring unit. The present invention constructs a node set of the entire production process of aluminum profiles and a blockchain of each node through blockchain technology, thereby ensuring that each production stage from raw material procurement to the final product has complete data recording and tracing capabilities.

The invention discloses a blast furnace incoming iron management data processing system and method. Comprising a data display module, a query module, an export module and a data operation module. The data display module is provided with a converter molten steel receiving display unit, a molten steel receiving team statistical display unit, a blast furnace incoming iron scrap display unit and a blast furnace incoming iron team statistical display unit; and the converter molten steel receiving and displaying unit is used for displaying detailed data received by the converter, wherein the detailed data comprises converter heat, blast furnace heat, time, ladle number, molten iron components and operation information. According to the invention, by integrating blast furnace incoming iron related data and intensively displaying various types of data on different pages, unified management of the data is realized. Meanwhile, convenient data entry, modification and deletion operation and efficient query and export functions are achieved, the time and labor cost of data management are greatly saved, and the data management efficiency is improved.

The utility model relates to the technical field of engineering machinery, in particular to a crane safety sensing system and a crane. The device comprises a cargo boom, a balance arm, a moving trolley and a plurality of acquisition devices, a first acquisition device in the plurality of acquisition devices is positioned on the cargo boom and is used for performing data acquisition on an area formed by horizontal rotation of the cargo boom; a second acquisition device in the plurality of acquisition devices is positioned on the balance arm and is used for performing data acquisition on an area formed by horizontal rotation of the balance arm; and a third acquisition device in the plurality of acquisition devices is positioned below the moving trolley and is used for carrying out data acquisition on a three-dimensional space area formed in the vertical orientation direction of the moving trolley. Due to the fact that active sensing based on the horizontal rotation direction of the boom and active sensing based on the vertical direction of the trolley are achieved, safety sensing can be conducted on objects around the crane more effectively and comprehensively, and the accuracy of recognition and positioning is effectively improved.

The utility model discloses a laboratory sample conveying device which comprises a machine frame, a driving mechanism is fixedly arranged on the machine frame, the driving mechanism comprises a driving assembly and a rotating threaded rod, and the rotating threaded rod is in threaded connection with a conveying platform. The conveying platform comprises a threaded connecting seat, a mounting plate arranged on the threaded connecting seat and a bearing plate fixedly arranged on the mounting plate, a limiting sliding rail is arranged on the side, close to the conveying platform, of the rack, a linear bearing is arranged on the side, close to the rack, of the mounting plate, and the linear bearing is slidably arranged on the limiting sliding rail; and an elastic locking mechanism is arranged on the bearing plate. According to the utility model, the transportation platform is driven by the electric driving mechanism, so that the labor intensity of workers is reduced; experimental samples are fixed through the elastic locking mechanism, production accidents caused by overturning of the samples in the transportation process are avoided, meanwhile, the transportation platform is limited through the limiting sliding rail, potential safety hazards are eliminated, and 5s sanitation is kept.

The application discloses a GIS partial discharge pattern recognition method based on polar coordinate distribution entropy optimization, and belongs to the field of large power grid on-site power equipment defect diagnosis and recognition. Firstly, aiming at the signal missing phenomenon of photoelectric partial discharge signals, a non-subsampled contourlet transform is used to fuse and process photoelectric PRPD graphs, so that photoelectric fusion graphs are obtained. Then, feature points and scale vectors of the fusion PRPD graphs are extracted based on a KAZE algorithm. Next, the feature points are dispersed to polar coordinate expressions according to coordinates and scale vectors. Distribution entropy of each region divided on the polar coordinates is calculated to form a feature vector. Finally, the feature vector is loaded into a long short-term memory network optimized by an Adaboost algorithm to verify the accuracy of partial discharge pattern recognition. Compared with a statistical parameter method and a KAZE feature extraction method, the algorithm can better extract a PRPD graph feature vector, and the accuracy of partial discharge defect pattern recognition is significantly improved.

The invention provides a software release processing method and device, electronic equipment and a storage medium, and can be applied to the technical field of software processing. The method comprises the following steps: acquiring a software code change task list and a task identifier, wherein the software code change task list is used for recording operation task information released by software; and mounting the software code change task list to a release list according to the task identifier, wherein the release list is used for displaying the operation state of the software release task. According to the method, after the task identifier and the software code change task list recording the operation task information released by the software are obtained, the software code change task list is mounted to the release list according to the task identifier, so that the release list can automatically record the operation state of the software release task; therefore, the software publishing staff can know the publishing process in time through the publishing list, and the sorting workload of the published information is effectively reduced.

The invention provides a protective helmet with on-site environment perception ability, which comprises a helmet body provided with a helmet shell, a lining and a wearing structure, the helmet body is connected with a face breathing unit, the face breathing unit is provided with an exhalation valve seat, the exhalation valve seat is provided with an air exhalation interface, and the helmet shell is provided with an air inlet and an air outlet. The exhalation valve seat is connected with an air respirator high-pressure air cylinder assembly through an air supply pipeline, environment sensing units are arranged on the top and the inner side of the helmet body in a scattered mode, a communication unit is arranged at the tail of the helmet body, the environment sensing units are electrically connected with the communication unit, and energy supply modules are arranged on the two sides of the helmet body. And the energy supply module is electrically connected with the environment sensing unit and the communication unit to supply power. According to the invention, on-site videos and audio information of operating personnel can be quickly acquired, data transmission is timely completed through a special communication network, meanwhile, head and respiratory tract protection under nuclear emergency conditions is provided, and the problems of data acquisition communication and respiratory protection of the protective helmet can be effectively solved.

The lithium battery pole piece baking oven (1) is characterized in that the lithium battery pole piece baking oven (1) comprises an oven body (2), an oven door (5), a heating device (6) and a circulating device (7), the oven body (2) is composed of an outer oven body (3) and an inner oven body (4), the oven door (5) is arranged on the front side of the oven body (2), and the heating device (6) is arranged on the inner side of the oven body (2). The heating device (6) and the circulating device (7) are arranged on the rear side of the outer box body (3), a pole piece inlet (8) is formed in the upper surface of the outer box body (3), a pole piece outlet is formed in the lower surface of the outer box body (3), and plate components (9) are arranged on the two sides of the pole piece inlet and / or the pole piece outlet respectively. The plate component (9) is fixed on the upper surface and / or the lower surface of the outer box body (3) through a long round hole (10) in a manner of adjusting the size of the pole piece inlet and / or the pole piece outlet.

The invention discloses a production management control system based on the Internet of Things, and relates to the technical field of injection molding machines, and the system collects production data in real time through an injection molding machine data collection server, and transmits the production data to a database server for storage through an Internet of Things module. And the IIS server provides a data access interface and supports remote access and monitoring of the injection molding station working panel, the mobile terminal and the billboard module. The system has the functions of data preprocessing, encrypted transmission, data backup and recovery and the like, and data security and accuracy are ensured. The billboard module displays the production data in real time and gives an alarm in case of abnormality, thereby improving the management efficiency. The injection molding station working panel and the mobile terminal support multi-platform operation, and remote management is facilitated. According to the invention, comprehensive monitoring and intelligent management of the production process of the injection molding machine are realized, the production efficiency is improved, the operation cost is reduced, and the product quality and the intelligent management level are remarkably improved.

The present application provides a video playback method, device, equipment and computer-readable storage medium; the method includes: playing the video content of a target video in a playback interface; in the process of playing the video content, when there is an associated video associated with the currently played video content, presenting association indication information containing a video thumbnail of the associated video; wherein the association indication information is used to indicate that the video corresponding to the video thumbnail has an association relationship with the currently played video content; based on the presented association indication information, when a trigger operation for the video thumbnail is received, the associated video corresponding to the video thumbnail is played. Through the present application, the viewing operation of the associated video can be simplified, saving the user's operation cost and time cost.

The invention relates to the technical field of nano silicon preparation, in particular to a nano silicon particle preparation device which comprises a muffle furnace used for heating reaction raw materials including magnesium powder and silicon dioxide powder; the stainless steel container is located in the muffle furnace, and the stainless steel container is used for containing reaction raw materials; one end of the thermocouple is connected to the interior of the stainless steel container through a wire, and the other end of the thermocouple is connected to the data collector; and the display is connected with the data acquisition unit. According to the preparation device of the nano silicon particles, the real-time reaction temperature of the reaction raw materials in the stainless steel container is fed back through the thermocouple, and the real-time reaction temperature is displayed on the display after being processed by the data collector, so that a worker can know and monitor the real-time reaction temperature in time, and the preparation success rate of the nano silicon particles is improved.

The invention discloses a wide-area thunder and lightning positioning management system with multiple propagation paths. The wide-area thunder and lightning positioning management system comprises a digital thunder and lightning detection station which collects related data of cloud-to-ground thunder and performs classification marking; the central processing analysis base station records the occurrence time of cloud-to-ground lightning stroke, marks the time period of single cloud-to-ground lightning stroke and generates a lightning stroke time period value; marking a cloud-to-ground lightning stroke area appearance position on a corresponding area map, and linearly connecting adjacent cloud-to-ground lightning stroke point coordinates to generate a lightning stroke area face value; combining the lightning stroke area face value and the cloud-to-ground lightning stroke time period of each quarter, and calibrating an overlapping area to obtain the frequent lightning stroke occurrence time period and position of each quarter; the propagator sets the propagation path of the calibration signal in the base station and the classification of the audience group, and stores the classification signal value in the first-level server and the second-level server. The technical problems that an existing system cannot carry out regional marking on lightning stroke line time, a lightning signal propagation path is single, and few audiences are covered are solved.

The invention belongs to the technical field of aquaculture, particularly relates to mobile intelligent feed feeding equipment for aquaculture, and aims to solve the problem that aquatic products cultured at present are not uniformly distributed in ponds and lakes and cannot ensure that aquatic product seedlings can be full of feed during feeding, and the following scheme is provided: the mobile intelligent feed feeding equipment comprises a mobile seat, a groove expanding plate is fixedly arranged at the top end of the movable seat, one side of the movable seat is ship-shaped, a driving paddle is arranged in the middle of the other side of the movable seat, and boosters are arranged at the two ends of the other side of the movable seat. According to the invention, the route guiding instrument and the distance measuring instrument work cooperatively to enable the feeding equipment to move along the water side of the aquaculture pond and make a vortex-ring-shaped advancing route according to the shape of the pond, so that the quantity of aquatic organisms underwater and on the water surface of the advancing route can be monitored and pre-judged, and then the feed guiding amount is adjusted by adjusting the rotating speed of the driving motor; and the feed scattered by the feed scattering nozzle can be conveniently added according to more aquatic organisms at local parts, so that the phenomenon that the aquatic seedlings cannot eat the feed fully is avoided.