228 results about "Technology analysis" patented technology

The invention discloses a construction site safety risk intelligent early warning system and method based on BIM and big data analysis, relates to the technical field of building engineering construction safety, and solves the problem that it is difficult to transmit construction site multi-source data which is collected and preprocessed in real time in real time and carry out space mapping with a BIM model. A rule engine is difficult to carry out initial early warning; a machine learning model is difficult to analyze time series data, predict collapse risks and identify dangerous behaviors; a risk prediction model is difficult to construct and is difficult to integrate into a BIM model; and pushing and closed-loop management are difficult to carry out on the risk early warning information. According to the method, the multi-source data is collected at the construction site, the digital twinborn scene is constructed by mapping the multi-source data to the BIM model by means of space-time alignment, the multi-source data is analyzed and processed by applying technologies such as a rule engine and a machine learning algorithm, and the result is integrated to the BIM model, so that visual risk monitoring and early warning are realized.

The invention discloses a virtual power plant optimization system and method, and the system comprises a virtualization platform module which is used for integrating distributed energy, energy storage equipment, an electric vehicle, a flexible load and other resources, and achieves the virtualization and centralized management of the resources; the dynamic resource aggregation module is used for dynamically matching resource characteristics with power system requirements; the market transaction module is used for optimizing the earnings of the virtual power plant; and the core algorithm module is used for optimizing the load prediction precision. The market transaction module implements two-stage market bidding based on a multi-agent game model, analyzes the uncertainty of quotation of competitors through a multi-scene simulation technology, optimizes a dynamic transaction strategy, and achieves the maximization of spot market benefits and the controllability of risks. Through cooperative work of a virtualization platform module, a dynamic resource aggregation module, a market transaction module, a core algorithm module, a security management module and the like, efficient management of resources and maximization of market benefits are realized.

The invention relates to the technical field of teaching quality evaluation, and particularly discloses a teaching quality comprehensive evaluation system and method based on a teaching sequence perspective, and the system comprises a data management module, a learning sequence analysis module, a teaching sequence analysis module, a teaching quality evaluation module, a feedback improvement module, and a decision support module. The data management module is used for collecting data generated in an education and teaching process, including learning sequence data of students and teaching sequence data of teachers, and performing arrangement and standardization processing on the collected data; the learning sequence analysis module is used for analyzing learning sequence data of the students through a data mining technology; according to the invention, by integrating the student learning sequence data and the teacher teaching sequence data and combining a data mining technology and a deep learning algorithm, key factors influencing the teaching quality are accurately identified, the teaching quality is objectively evaluated in a data-driven manner, the deviation of manual evaluation is avoided, and the teaching quality is accurately evaluated. And the transparency and fairness of teaching quality evaluation are enhanced.

The invention discloses a water conservancy project building full life cycle management method based on BIM technical analysis, and relates to the technical field of building full life cycle management. And respectively constructing three structural indexes, namely a microcrack expansion rate index F1, a damp-heat permeation combined degradation index F2 and a dynamic stiffness phase deviation index F3. The multi-dimensional feature system not only covers key risk sources such as material microcosmic degradation, environmental coupling effect and mechanical response mutation, but also breaks through a traditional extensive method which depends on single sensing data to perform health judgment, and provides a digital expression model with physical interpretation force for structural risks. According to the method, a unified health data standard system is established, and the health data standard system can be used as a core data source of upper-layer applications such as dynamic structure evaluation, an early warning model and visual mapping.

The invention relates to a man-machine interaction dialogue method, system and device based on a natural language and a medium. The method comprises the steps that firstly, multi-modal interaction data is acquired and preprocessed, and segmented words and syntax are analyzed through a natural language processing technology to construct intention feature vectors; combining the intention feature vector with a historical dialogue record, and using a pre-trained language model to generate context semantic elements containing a semantic relationship; if the context semantic elements are matched with the preset scene feature library information, predicting a user intention change trend by adopting a reinforcement learning model to obtain an intention prediction result; and finally, evaluating user intention change based on an intention prediction result, extracting associated domain knowledge by utilizing a knowledge graph if significant change occurs, and inputting the associated domain knowledge into a dialogue generation model to obtain a natural language reply sequence. According to the method, the understanding precision of the user intention is improved, the dynamic prediction of the intention change is realized, the relativity and coherence of reply are guaranteed, and a more efficient processing path is provided for natural language man-machine interaction.

The invention discloses an enterprise digital operation real-time data analysis method based on multi-source data fusion, relates to the technical field of data processing, and solves the problems that firstly, an enterprise comprehensive benefit index is difficult to analyze and predict; secondly, it is difficult to embed the knowledge graph into a vector space to construct a dynamic graph neural network; then, the equipment abnormal offset, the supply chain abnormal offset and the customer activeness are difficult to analyze, a risk matrix is constructed, and a comprehensive benefit index decline propagation path is identified; service link resources are difficult to dynamically allocate according to an analysis result of the risk matrix; and finally, a data analysis result is difficult to display visually. According to the method, enterprise multi-source data is collected and preprocessed, a three-dimensional vector space and a dynamic graph neural network are constructed, enterprise benefits and risks are analyzed and predicted in combination with multiple technologies, resources of business links are dynamically allocated, and a data analysis result is visually displayed.

The invention relates to the technical field of food detection, and discloses a food pesticide residue safety detection analysis method based on machine learning, which comprises the steps of food sample collection, extract pretreatment, two-dimensional liquid chromatography-high resolution mass spectrometry combined technology analysis, mass spectrum acquisition, mass spectrum numerical data conversion, data correction and machine learning model establishment. The method comprises the following steps: identifying and classifying pesticide residue components, extracting a pretreatment extract, analyzing a to-be-detected sample, acquiring a mass spectrum, converting the mass spectrum into to-be-detected mass spectrum numerical data, correcting the data, inputting a model, identifying and classifying pesticide residues, quantitatively analyzing, comparing food safety standards, judging conformity and generating a detection report. The invention aims to improve the accuracy, sensitivity and efficiency of pesticide residue detection. Meanwhile, through technical correction and optimization, the problems of environmental interference, data deviation and the like faced by an existing method are effectively solved.

The invention discloses a technology development analysis method and system based on a patent big language model, and relates to the field of big data analysis. The problems that an existing artificial intelligence patent analysis method is difficult to accurately analyze a technical structure in a patent text, cannot describe a technical hierarchical relationship, is difficult to eliminate technical semantic diversity, cannot systematically analyze a technical evolution process and the like are solved. And the network structure characteristics and the technology node importance are analyzed, and the evolution characteristics of the technology system in different stages, the key technology nodes and the change trend of the technology community structure can be identified, so that technical support is provided for artificial intelligence technology development situation research and judgment and technology layout decision. The method is suitable for a technical analysis scene of million-level patent data.

The invention discloses an intelligent operation and maintenance method and system for an energy management platform, and relates to the technical field of intelligent operation and maintenance, and the method comprises the steps: analyzing data through employing an NLP technology, generating a multi-objective optimization function, constructing a user behavior portrait, adjusting the weight parameters of the multi-objective function through employing a reinforcement learning algorithm in combination with an Actor strategy network, and carrying out the operation and maintenance of a user. An energy scheduling scheme is obtained by using an improved bald eagle search algorithm and a prey escape energy mechanism, a digital twinborn model of mapping of a physical space and a virtual space is constructed, and the energy scheduling scheme is optimized and implemented by combining the digital twinborn model with a soft constraint mechanism. Through fusion of NLP technology semantic analysis and a reinforcement learning algorithm, a multi-target scheduling strategy is dynamically optimized, and an improved bald eagle search algorithm and a digital twin model are combined to realize simulation verification and closed-loop feedback, so that the intelligence and optimization level of energy system operation is improved, and the stability, economy and low-carbon operation capability of the system are also improved.

The invention discloses a knowledge graph construction method based on data assets, and relates to the technical field of artificial intelligence and knowledge management, and the method comprises the steps: collecting data assets, employing an adaptive data preprocessing technology, automatically recognizing and cleaning different types of data assets, and carrying out the fusion of multi-modal data through deep learning. Constructing an inference engine based on semantic understanding, analyzing data context by using a natural language processing technology, deducing an implicit relationship between data, and enhancing a relationship between entities in the atlas; the method comprises the following steps: deducing missing information in a knowledge graph through knowledge reasoning and a completion algorithm of a graph neural network, generating an interpretable knowledge graph, increasing the credibility of a user to the knowledge graph by recording a derivation process of a node and a relationship between nodes, and recording an updating process of the knowledge graph by utilizing a block chain technology. According to the method, the overall richness and accuracy of the knowledge graph are improved, the credibility and use convenience of the user to the knowledge graph are enhanced, and the information integrity and accuracy of knowledge are improved.

The invention relates to the technical field of photovoltaic energy storage, and provides a photovoltaic energy storage equipment remote AI monitoring method and system based on a management platform, and the method comprises the steps: obtaining an operation signal of energy storage equipment, carrying out the analysis and processing of the operation signal, and obtaining signal feature data and a signal abnormality index; performing trend analysis on the signal characteristic data to obtain a trend analysis result, and verifying the signal abnormal index by using the trend analysis result to obtain an abnormal verification result; inputting the abnormal verification result into a preset energy storage management system for analysis to obtain preliminary diagnosis information, and analyzing the preliminary diagnosis information to obtain a potential fault; and generating a corresponding fault alarm signal according to the potential fault, and generating a corresponding fault processing suggestion based on the fault alarm signal. By combining artificial intelligence and a data mining technology to analyze feature data and abnormal indexes of operation signals, the problems that data analysis is not intelligent enough and fault diagnosis precision is insufficient in practical application are solved.

The invention relates to the technical field of workflow construction, in particular to an AI workflow construction method and system based on image recognition and electronic equipment. The method comprises the following steps: recording a working process by using a video recording tool, collecting operation data, analyzing video content and extracting key frames and operation steps by adopting image recognition and natural language processing technologies, and performing time sequence division and behavior analysis on operation behaviors in combination with user operation event data so as to determine actual operation steps. The method comprises the following steps: generating a detailed step list with alliance tag information, then combining operation steps with video segments according to an analysis result to form a structured work flow, adding detailed description and annotation information for each step, and finally establishing an index structure, so that a user can quickly retrieve a required business flow video or document through keywords. According to the method, the visualization degree and the understandability of the business process can be improved, the learning cost is reduced, and the working efficiency is improved.

The invention discloses a nursing decision support system and a nursing decision support method, and relates to the field of health care, in the system, a data acquisition module is used for acquiring multi-source data in real time; the data processing module is used for integrating multi-source data by adopting a natural language processing technology and a data mining technology to obtain a unified data set; the graph construction module is used for taking each type of data in the unified data set as a knowledge node, analyzing association relationships among the knowledge nodes by adopting a data mining technology, endowing each association relationship with a weight value, and constructing a knowledge graph according to the knowledge nodes, the association relationships and the weight values; the dynamic updating module is used for regularly updating the knowledge graph according to the currently acquired multi-source data; the decision support module is used for calling the current knowledge graph to generate nursing measures of the patient, comprehensive, accurate and real-time nursing decision support can be provided, and the nursing experience and nursing quality of the patient are improved.

The invention discloses an airport aircraft variable anti-collision protection area construction early warning method and system and electronic equipment. The method comprises the steps that S1, a multi-level anti-collision protection area basic standard model of an aircraft is constructed in an airport map model; s2, collecting motion sequence data of the aircraft in a time period t1 before the current moment, and inputting the motion sequence data into the LSTM data prediction model to predict motion sequence data of the aircraft in a time period t2 after the current moment; s3, extracting motion sequence data of the time period t1 to adjust the sizes of the emergency collision avoidance area, the early warning monitoring area and the adjacent risk area; collecting the vehicle speed in the vehicle motion sequence data and the speed and course data in the motion sequence data in the time period t2 to calculate the relative distance and the relative speed of the vehicle and the aircraft; and S4, the anti-collision early warning system judges and predicts whether falling into an adjacent risk area, an early warning monitoring area and an emergency collision avoidance area. According to the method, prospective anti-collision technical analysis is realized, and the airport safety operation margin is improved.

The invention belongs to the field of medical technology analysis, and discloses an analysis method and system for revealing a hidden binding pocket of a drug target, and the method comprises the steps: firstly obtaining a representative conformation metastable state of a target protein through conventional molecular dynamics simulation and clustering analysis; secondly, constructing a Markov state model to analyze a dynamic transformation rule between conformations; carrying out enhanced sampling by adopting meta-dynamics, and deeply exploring a rare conformation space; and finally, constructing a free energy landscape to quantitatively evaluate the relative stability of the conformation, and identifying a hidden binding pocket in the stable rare conformation. According to the method, the limitation of a single calculation means is overcome, a full-chain calculation system of dynamic conformation analysis-hidden cavity feature mining-novel ligand rational design is constructed, and the formation mechanism and potential druggability of the hidden pocket can be comprehensively revealed from the two dimensions of dynamics and thermodynamics; and an efficient and accurate calculation framework is provided for research and development of innovative drugs targeting difficult drug targets.

The invention relates to the technical field of intelligent testing, and discloses a software test task management method and device based on an intrusive instruction knowledge base, equipment and a medium, and the method comprises the steps: analyzing an obtained demand card based on a large model technology, analyzing a semantic role of a vocabulary in the demand card through a semantic role labeling technology, and obtaining a semantic role of the vocabulary in the demand card; extracting test requirements and test points of semantic roles of vocabularies in the requirement cards; querying test information matched with the test requirements and the test points in a knowledge base of the software project, and determining the test information with the highest matching degree as target test information; in combination with the demand card and the target test information, automatically generating a test scheme of the current version based on a large model technology; and according to the generated test scheme. The method can be applied to the development of business systems such as financial science and technology, medical health, old-age care and the like, and the efficiency of the test work is remarkably improved by automatically analyzing the demand card, generating the test scheme and arranging the test task.

The invention relates to the technical field of low-altitude aircraft attitude control, in particular to a low-altitude aircraft attitude control system based on intelligent information data analysis. The method comprises the following steps: a data acquisition and storage unit acquires aircraft data and environmental parameter data; the intelligent information analysis unit analyzes the real-time attitude of the aircraft by using a nonlinear dynamics technology and a singular perturbation theory technology, and judges whether the aircraft is in a safe state or not by using a singular perturbation analysis technology; the single aircraft control unit generates an optimal control strategy by using a linear quadratic regulator in combination with an advanced attitude control algorithm; the multi-aircraft control unit adopts a distributed control strategy to control coordinated flight among the aircrafts; and the control display terminal unit is used for providing an integrated human-computer interaction interface. According to the low-altitude aircraft attitude control system based on intelligent information data analysis, nonlinear dynamics and singular perturbation theories are combined, and cooperative flight control of a single aircraft or multiple aircrafts is realized by adopting a distributed control architecture.

The invention provides a fishery resource dynamic monitoring method and system based on underwater detection equipment, relates to the field of dynamic monitoring technology analysis, and realizes fine management of water area monitoring by collecting fish school density data in real time, constructing a fish school density matrix and combining grid unit division and geographical hash coding. The gradient value of the adjacent grid units is calculated based on the density matrix, the gradient matrix is generated, the fish school density abrupt change area can be accurately recognized, the abnormal area is marked, then the sonar sampling frequency of the underwater detection equipment is dynamically adjusted, and the monitoring precision of the abnormal area is improved. Compared with the prior art, the method has the advantages that the monitoring precision, the anomaly detection response capability and the resource utilization efficiency are remarkably optimized, and the adaptability and the prediction capability of a monitoring system are improved particularly in the aspects of fish swarm migration trend prediction and grid division dynamic adjustment.

The invention relates to the technical field of business and financial fusion data security interaction scheme design based on credential creation, in particular to a business and financial fusion data security interaction method and system based on credential creation. The method comprises the steps of collecting, standardizing, storing and encrypting business and financial data, constructing a dynamic access control rule base by utilizing multi-dimensional information and a machine learning algorithm to carry out accurate access control, adding an identifier and a timestamp for interactive data, realizing data tracing through a block chain, and realizing data tracing through a block chain. And analyzing the operation log and the data traceability information by adopting a natural language processing and machine learning technology to perform exception auditing. The system comprises a data acquisition module, a standardization module, a storage module, an encryption module, a dynamic access control module and a data traceability auditing module. According to the invention, the data security and management efficiency of the business and financial fusion system are improved to a great extent, and the problems of inaccurate dynamic access control, difficult data tracing and emerging technology fusion are solved.

To provide a system.SOLUTION: The system includes: means for automatically generating a business document from an instruction; means for checking a grammatical error in the generated business document; means for checking compliance of the generated business document; means for determining whether the generated business document conforms to the standard of a business communication; analyzing the generated business document by using a natural language processing technology; and means for repairing the business document on the basis of the result of analysis.SELECTED DRAWING: Figure 1

The invention discloses a new energy automobile fault diagnosis system based on an AI intelligent model, and the system comprises the steps: collecting the dynamic, static and historical data of an original automobile through a data collection module, obtaining a real-time data flow through the combination of a diagnosis box and an OBD interface, and integrating the local or cloud static data; the AI model data module is connected with the data acquisition module and is used for supplementing fault data and maintenance records of vehicle enterprises, maintenance sites, 4S stores and the like, and the multi-dimensional data processing module is used for carrying out data association analysis, mining hidden relationships and constructing a multi-dimensional feature matrix; the AI model data processing and decision analysis module processes multi-source data, analyzes the data by using technologies such as a knowledge graph and a long-short-term memory network, and adapts to a new vehicle type through transfer learning; and the AI diagnosis report module is used for matching faults and reasoning roots, generating a report containing maintenance suggestions, and also has predictive maintenance and emergency processing functions, so that efficient and accurate diagnosis is realized.

The invention relates to a digital teaching system based on a multi-mode intelligent technology. A teaching end displays digital content through screen equipment; the control end provides a digital classroom control capability for teachers or assistant teachers through mobile equipment; the student end realizes real-time interaction between students and the digital classroom through a mobile device configured with a voice device; the server is configured with an intelligent knowledge base, analyzes classroom data based on an intelligent algorithm and a big data analysis technology, generates a learning path and recommendation resources according to student conditions, processes questions with the help of natural languages, and drives the whole teaching to operate intelligently. According to the invention, classroom interaction intellectualization can be realized, teaching quality can be improved, multidisciplinary knowledge coverage and dynamic adaptation can be realized based on an intelligent knowledge base, modular course design and dynamic interaction are optimized, dialogue type and touch type interaction modes are fused, popularization application of code-free teaching design is supported, and teaching experience is improved. And classroom effect optimization driven by real-time data, enhanced teaching feedback and long-term improvement are facilitated.

The invention relates to computer-implemented systems and methods for implementing an application modernization and migration tool. The invention provides: initiating a discovery of current system specifics, wherein the discovery comprises business analysis and technical analysis; based on the discovery, developing a modernization plan that prioritizes and optimizes application and system migration, wherein the modernization plan considers risk analysis and cost estimation; designing a pathway and an architecture for the modernization plan; executing the pathway and implementing the architecture to initiate a modernize and migrate process for a target system wherein the modernize and migrate process comprises one or more of: infrastructure build, data migration, rebuild, rehost, re-platform, refactor and integrations, testing and delivery; and making available operation of the modernized and migrated target system.

The invention relates to a review system and method based on an adaptive scoring algorithm and multi-modal analysis, in particular to the field of college student innovation and entrepreneurship competition review, and the system specifically comprises a data input processing module, an automatic scoring calculation module, an expert review simulation module and an auxiliary decision support module. According to the technical scheme, the scoring weight and the standard can be dynamically adjusted according to the specific requirements and the standard of the contest, through the machine learning technology, historical review data are analyzed, key review factors are identified, the scoring model is automatically adjusted according to the characteristics and the target of the current contest, and the self-adaptive capability enables the review system to more accurately evaluate the competing works, so that the quality of the competing works is improved. And meanwhile, human prejudice is reduced.

The invention provides a scene recognition and value-added service adaptation system and method based on a 5G new call, and aims to improve the intelligence and automation level of the 5G call. The system comprises a service control processing module, a service function intelligent selection module, a voice media processing module, a video media processing module, an AI intelligent identification module, a user interface module and an RTP processing module. User behaviors and call content are analyzed through the AI technology, and the system can automatically recognize call scenes and intelligently select corresponding value-added services such as real-time translation, voice transcription and virtual background. The user interface module optimizes scene recognition and automatic switching functions, provides a value-added service control panel and personalized setting, supports voice instruction operation, and realizes efficient interaction between a user and the system. The system can seamlessly integrate the value-added service into the call media stream, dynamically adjust the service to adapt to the change of the call scene, and continuously optimize the call experience of the user.

The invention discloses a financial futures market condition analysis method and system based on multi-agent collaboration. The method comprises the steps that structured data including market data, news information and social media emotion are collected in real time; carrying out technical index technology and trend analysis and supporting resistance potential identification by adopting indexes including a moving average line, a relative strength index RSI, an exponential smoothing different and similar moving average line MACD and a Boforest belt, and outputting a technical analysis report; a basic analysis report is output by analyzing the financial statement, the macroeconomic data and the industry dynamics; the method comprises the following steps: analyzing market emotion, news emotion and social media public opinions by adopting a natural language processing method and an emotion analysis method to obtain market emotion indexes; and generating executable prediction and investment suggestions by integrating the technical analysis report, the basic analysis report and the market emotion indexes. According to the method, the problems of limitation of a single model, data islands, insufficient real-time performance and the like in the prior art are solved.

The invention belongs to the technical field of network equipment management, and particularly relates to a router unified configuration and debugging method and device, electronic equipment and a storage medium. Comprising the following steps: constructing a protocol analysis model to analyze and process data packets of different protocols and standards; establishing a database with complete equipment models, constructing a command library, and analyzing and classifying different types of commands; user input is analyzed by using a natural language processing technology, user input habits and common commands are recorded through a machine learning algorithm, and personalized command recommendation is provided; a standardized operation process is designed, and the links of configuration, debugging, monitoring and fault processing of the router are covered; implementing identity verification, access control and data encryption measures, and monitoring and reporting security risks in the network in real time; according to the invention, multi-protocol support, standardized operation flow, automatic configuration and monitoring, intelligent fault processing and safe data management can be realized, and the efficiency and accuracy of network management are improved, so that the manual intervention cost is reduced.

The present invention discloses a device and method for testing the combined action mechanism of visual abrasion based on ultrasonic cavitation, comprising a stirring water tank, the top of which is connected upwardly to a transparent water tank, a sediment circulation pump being provided in the stirring water tank, the sediment circulation pump being connected to a cavitation generator with a bottom opening and extending into the top of the transparent water tank through a pipe extending upwardly from the stirring water tank, a specimen mounting fixture being provided below the cavitation generator and a PIV shooting device, a high-speed camera shooting device, and shooting auxiliary equipment being provided on the outside of the transparent water tank, all of which are electrically connected to a synchronizer and a computer. The present invention uses a single experimental device to conduct multi-angle cavitation, erosion, wear, and abrasion experiments, thereby better comparing and analyzing the four types of hydraulic mechanical damage. At the same time, dynamic capture is performed through high-speed camera and PIV technology analysis to analyze the effects of different hydraulic conditions on different damage processes and microscopic development mechanisms.

The invention relates to the technical field of reclaimed water treatment, in particular to a reclaimed water treatment system decision-making method based on data analysis, which comprises the following steps of: firstly, acquiring related data at each key node in a reclaimed water treatment system by using an acquisition system, and preprocessing the acquired related data of each key node in the reclaimed water treatment system; then constructing a water quality prediction model by adopting a machine learning algorithm on the basis of the pre-processed related data, inputting historical water quality parameters and equipment operation parameters in the reclaimed water treatment system into the water quality prediction model for prediction, predicting a water quality change trend in a period of time in the future, and then adopting a data mining technology to predict the water quality change trend. The method comprises the following steps: analyzing the correlation among equipment operation parameters and the relationship between water quality parameters and the equipment operation parameters to determine key factors influencing the treatment effect of the reclaimed water system, and finally making a decision strategy of the reclaimed water treatment system based on the key factors influencing the treatment effect of the reclaimed water system and the water quality change trend in a period of time in the future. The problems that a reclaimed water treatment system is poor in decision-making accuracy and decision-making timeliness, and energy conservation, consumption reduction and operation optimization of the reclaimed water treatment system cannot be achieved are solved.

The intelligent apple planting management and expert decision-making system comprises a sensor data acquisition module, an image data acquisition module, an edge calculation module, an expert knowledge module, an intelligent analysis module, an expert decision-making module, a wireless communication module, an equipment control module, a growth data tracing analysis module and a user interaction control module. Environmental and growth data are collected through a sensor and an image data acquisition module, and are transmitted to an edge calculation module through wireless communication. The system combines artificial intelligence technology analysis and expert knowledge, evaluates the growth condition of fruit trees, provides a scientific planting strategy, supports automatic control of agricultural operations such as irrigation and fertilization, realizes full-cycle tracing and optimization of growth data, and aims to provide more accurate production management parameters for planters, provide decision basis for scientific and standardized production, and improve the production efficiency. Apple quality is improved, diseases are reduced, planting management is optimized, and orchard production benefits are increased.