91 results about "Information coverage" patented technology

The invention discloses a hierarchical semantic-driven retrieval enhancement generation method and system, a natural hierarchical relationship and a semantic boundary of a document are effectively reserved by constructing a tree hierarchical structure based on a document chapter title, and a recursive semantic boundary splitting strategy is adopted to refine overlong text nodes, so that the semantic integrity is ensured, and the retrieval enhancement generation efficiency is improved. And the model input length limitation is met, and the semantic information is prevented from being lost. Meanwhile, node knowledge point extraction and abstract generation are achieved through a large language model, top-down multi-level title path transmission and bottom-up content aggregation are combined, the structural perception and semantic expression ability of nodes is enhanced, and in the retrieval stage, based on similarity distribution of query and node semantic expression, an adaptive retrieval threshold value is dynamically calculated, and the retrieval efficiency is improved. A fixed top-k retrieval strategy is replaced, intelligent screening of different query and hierarchical nodes is achieved, information coverage and redundancy suppression are balanced, and retrieval efficiency and accuracy are remarkably improved.

A spatial omics multi-modal fusion method under a single cell level comprises the following steps: extracting spatial morphological characteristics of differential expression genes and cell nucleuses from spatial transcriptome data, single cell sequencing data and histological images, and realizing field adaptation among different platforms by using a conditional variation auto-encoder. And based on a probability inference model, fusing spatial transcriptome expression, unicellular omics and morphological characteristics, and jointly inferring the type and gene expression level of each cell. A spatial cell network is constructed through a graph attention mechanism, and spatial diffusion and recognition of cell types in a full slice range are realized. In combination with a multi-omics enhancement module, undetected gene and protein expression is completed based on expression similarity, and prediction consistency is improved through spatial correction. According to the method, high-resolution reconstruction of single-cell multi-omics information in a three-dimensional space is realized, the information coverage and spatial resolution of spatial omics data are improved, and an efficient and low-cost solution is provided for spatial biology and precise medical research.

The invention discloses a relational database-oriented data retrieval enhancement generation method and system, and relates to the technical field of internet data retrieval services. The relational database-oriented data retrieval enhancement generation method comprises the following steps: S1, collecting original structure data, meta-information data and semantic interference data, and constructing a standardized multi-granularity expression set after preprocessing; s2, analyzing a semantic structure queried by a user, and dynamically adjusting an information extraction range according to the semantic structure; s3, comprehensively evaluating field matching strength and time coverage suitability, and switching a context construction strategy; s4, evaluating the semantic integrating degree and the information coverage degree of the candidate segments, and constructing a multi-level prompt context structure; and S5, tracking the semantic granularity and the context adaptation degree, and performing response quality diagnosis and dynamic correction. The problems that in a relational database, natural language query semantic granularity is difficult to switch in a self-adaptive mode, structure fragment matching is not accurate, and context prompt construction is redundant and scattered are solved.

The invention relates to the technical field of image focus detection, in particular to a fiber endoscope image focus detection method and system, and the method comprises the following steps: providing a data quality guide interface; capturing narrow-band light images of the endoscope away from a first preset position and a second preset position of the intestinal wall in the axial movement process, calculating brightness gain values of a blue light channel and a green light channel, calculating an asymmetric scattering correction coefficient, and updating indication of color information calibration integrity; tracking the pixel moving speed of the interferent in the view in the propulsion operation process, calculating the relative depth of the interferent, and updating the indication of the validity of the depth data of the interference layer; identifying the image area which is not shielded by the interferent, and updating the indication of the information coverage degree of the background area; triggering an image synthesis operation; performing color compensation on the image information of the image area which is stored in the background canvas and is not shielded by the interferent; reconstructing a clear image; and performing focus detection on the clear image. The method improves the accuracy of focus detection.

The invention relates to the technical field of constructional engineering informatization, and discloses an engineering consultation management system based on big data. Collecting data of material declaration price, market average price, project submission amount, project review amount, change amount cumulant, contract initial amount, project payment paid proportion and project actual completion progress in project cost through access of multi-source heterogeneous data; and the data processing module is used for processing and analyzing the data acquired by the data acquisition module so as to calculate the deviation condition of the material unit price, the deviation condition of the engineering quantity, the density condition of the change signature and the payment deviation condition of the progress money. According to the method, comprehensive collection of multi-source heterogeneous data is adopted, the problem that a traditional system is single in data source is solved, the information coverage range is widened, and false or missing information in the project cost is rapidly judged through an integrated calculation engine.

The invention provides an RAG adaptive evidence refining method based on submodule optimization, and belongs to the technical field of artificial intelligence. Collecting data to construct a knowledge base, and generating a candidate document set according to the knowledge base inquired and retrieved by a user; designing an instruction and calling a DeepSeek model to evaluate the answer contribution degree of the candidate document, calculating the relevancy between the query and the candidate document and the information coverage degree score of the optimal document to the candidate document, and constructing a sub-module objective function; calculating a marginal gain threshold value, iteratively calculating optimal documents with marginal gains greater than the threshold value, and generating an optimal document set; and splitting the optimal document set according to the paragraph level, generating a candidate paragraph set, calculating the redundancy score of the optimal paragraph set, constructing a sub-module objective function added with redundancy penalty by multiplexing the method, and performing iterative calculation to generate a final optimal evidence paragraph subset. The method effectively solves the problems of over-high redundancy, over-low information coverage and the like caused by a traditional processing method, so that the final model reasoning performance is improved.

The invention discloses an equipment information management method and an equipment information management device, and relates to the technical field of server hardware management, and the method comprises the steps that VPD information is read in a manner of enumerating PCIe equipment through a BIOS, the VPD information is an inherent attribute of the equipment and is extracted by the BIOS at the beginning, comprehensive coverage of basic information of the equipment is guaranteed, and the equipment information is stored in the BIOS; the BMC reads FRU information of equipment by using an I2C bus and an SMBus, covers function information of the equipment, reads data through the BMC, makes up for the defects of VPD information in function description and state monitoring, combines the VPD information obtained by the BIOS and the FRU information obtained by the BMC to form a target information set, the target information set comprises equipment manufacturing information and function information, and the equipment manufacturing information and the function information are stored in the BMC. Omnibearing information coverage of the PCIe equipment is realized, and the technical problem that the coverage range of information acquired by the PCIe equipment in the prior art is not comprehensive is solved.

The invention relates to the technical field of risk portrait generation based on a knowledge graph, and discloses a risk portrait generation method based on the knowledge graph. According to the scheme, the document is segmented through the sentence end symbols, semantic coherence is ensured, and the accuracy and stability of candidate word extraction are improved. Continuous Chinese character sequence segmentation is adopted, dependence of a word segmentation tool is avoided, the occurrence frequency and position of candidate words are recorded, and a detailed statistical basis is provided for risk factor screening. A minimum occurrence number constant is set, noise interference and information coverage are balanced, the screening flexibility is improved, and candidate word screening is more representative. And counting the co-occurrence relationship of candidate words in the sentence, quantifying the co-occurrence frequency through an indicator function, enhancing word association expression, and providing key data for initial graph construction. Finally, the scheme constructs a knowledge graph based on the candidate words and the co-occurrence relation thereof, ensures clear expression of risk information, and improves the accuracy of the system in risk identification and portrait generation.

The invention discloses a data query method, system and equipment based on distributed retrieval enhancement generation, and belongs to the field of data processing. The method comprises the following steps: a first node receives a query request initiated by a user through a gateway; the first node sends a query request to at least one second node through the gateway; the first node and the second node retrieve own knowledge bases respectively to obtain candidate documents matched with the query request, and generate retrieval results based on the candidate documents through own gateways; the second node sends a retrieval result generated by the second node to the first node through the gateway; the first node reorders the retrieval result generated by the first node and the retrieval result sent by the at least one second node through the gateway, and determines a target retrieval result based on the reordering result; and the first node generates a query result corresponding to the query request based on the target retrieval result through the large model. According to the embodiment of the invention, the information coverage rate and the scene adaptability can be improved, so that the accuracy of the query result is improved.

The invention relates to a document analysis and retrieval enhancement generation method fused with a multi-modal embedding model, and belongs to the technical field of AI large model application. The method comprises the following steps of: analyzing a file and extracting contents of texts, tables and pictures; performing joint semantic embedding on the extracted texts, tables and pictures by using a multi-modal embedding model to generate uniform vector representation, and constructing a vector database supporting multi-modal data; and constructing a multi-modal retrieval chain based on a vector retriever. According to the method, total element analysis and joint modeling of complex documents are achieved, the problem that multi-modal information is difficult to process in a unified mode through a traditional vectorization technology is solved to a certain degree, and the information coverage capacity and the answer accuracy of a retrieval enhancement generation system in a real scene are remarkably improved.

The invention discloses a retrieval enhancement generation method and system fusing multi-modal and hybrid retrieval, and relates to the technical field of multi-modal fusion and hybrid retrieval, and the method comprises multi-modal information fusion framework construction, row hybrid retrieval execution, adaptive weight distribution and context construction, and structured intelligent content compression and generation. According to the retrieval enhancement generation method and system fusing multi-modal and mixed retrieval, the limitation that a traditional RAG system depends on a single text vector library is broken through by integrating multi-source information, multi-modal information sources such as contract original texts, expert suggestions, dialogue history and external similar cases are integrated through a unified framework, the comprehensiveness of information coverage is ensured, and the retrieval enhancement generation efficiency is improved. According to the method, more abundant factual basis is provided for result generation, and for double guarantee of semantics and keywords, a parallel mixed retrieval method is adopted to be combined with vector retrieval and full-text retrieval, so that the defect of a single retrieval mode is avoided, and the accuracy and correlation of retrieval results are improved.

The invention discloses a dynamic risk assessment method based on multi-source heterogeneous data and application. The method comprises the following steps: extracting risk features from the multi-source heterogeneous data; constructing a multi-dimensional risk assessment model based on the labeled risk features; and based on the multi-dimensional risk assessment model, the risk is scored. According to the method, multi-source heterogeneous data can be effectively fused, risk features are extracted through a unified data processing flow, a multi-dimensional risk assessment model is constructed, risk scoring based on the multi-dimensional risk features is realized, the problems of coarse assessment granularity and insufficient information coverage caused by dependence on a single data source in the prior art are solved, and the risk assessment efficiency is improved. And the comprehensiveness and the accuracy of a risk assessment result are remarkably improved.

The invention provides a mobile terminal skin parameter inversion method based on spectral information, and the method comprises the following steps: constructing an optical model according to the characteristics of a skin layered structure and a spectral response mechanism of three skin parameters: melanin content, hemoglobin concentration and dermis thickness, and building a skin parameter and reflection spectrum database based on the model; based on the database, establishing a skin multi-parameter inversion MLP neural network structure adaptive to the collection characteristics of a mobile phone end sensor, and screening an optimal four-waveband channel through multi-waveband combination traversal; the mobile phone spectrum sensor is subjected to wave band optimization, data acquisition and skin parameter inversion. According to the method, through efficient decoupling of a nonlinear coupling relation among multiple skin parameters by waveband optimization and an MLP model, and targeted design of four optimal visible light narrow-band channels, synchronous quantitative detection of melanin, hemoglobin and dermis thickness is realized, core physiological parameters from epidermis to dermis superficial layer are covered, information coverage is comprehensive, and specificity is high.

The invention discloses a standard text semantic analysis and key clause extraction method and system, and the method comprises the steps: carrying out the multi-level semantic analysis of a standard text, recognizing a to-be-evaluated clause and a corresponding type in the standard text, extracting a key parameter entity of the to-be-evaluated clause, and constructing a clause-level semantic association structure; based on the semantic association structure, a standard term parameter knowledge graph is constructed, and the knowledge graph supports semantic query of technical parameters; and performing weight calculation and screening on the to-be-evaluated terms based on the standard term parameter mapping knowledge domain, and generating a structured standard requirement abstract list based on the screened key terms and associated parameter information in the corresponding mapping knowledge domain. In combination with multi-level semantic analysis and parameterized knowledge graph construction, automatic and structured extraction of standard text core requirements is realized, and the technical problems of low efficiency, incomplete key information coverage and lack of semantic association caused by dependence on manpower or shallow text processing are solved.

According to the multi-source retrieval and agent collaborative decision-making medical question-answering system and method, a three-layer retrieval framework is constructed, a local medical knowledge base vector retriever, a PubMed intelligent retriever and an academic deep crawling device are integrated, dynamic fusion of multi-source heterogeneous medical information is achieved, and the medical question-answering efficiency is improved. Through the synergistic effect of the three, the information coverage range is remarkably expanded, more comprehensive and multi-dimensional evidence support is provided for various medical problems, the retrieval efficiency and accuracy of a professional database are effectively improved, and the use threshold of non-professional users is reduced. Meanwhile, the technical scheme of the invention supports dual-scene task processing, can meet diversified medical information requirements, provides reliable reference for diagnosis and treatment decisions of medical staff, also provides structured and high-quality information support for subject investigation of medical researchers, and powerfully promotes intelligence and precision of medical information processing.

The invention relates to the technical field of information processing, in particular to a reverse order full-link identification and risk control method, device and equipment and a storage medium, and the method comprises the steps: regularly pulling order basic information of a merchant from a plurality of open APIs, and employing a CRF model to identify a waybill reverse label in the order basic information, cross-platform reverse order data streams are automatically processed, the multi-source heterogeneous data integration capability is achieved, the data processing efficiency is improved, accurate recognition and standardized management of reverse order customer information are achieved, sending and receiving information corresponding to reverse waybill numbers is inquired, whole-process processing of order data is covered, the data management quality is improved, and the data management efficiency is improved. Calling a naive Bayesian classification model to calculate a first risk probability of the sending and receiving information, improving the intelligent degree of risk identification, fusing the first risk probability and the historical total return rate of the user to obtain a second risk probability, and generating abnormal order interception information when the second risk probability is greater than a preset risk threshold value. And risk control decision-making efficiency is improved.

The invention provides a dynamic optimal rotating target detection method based on a multi-view image of an unmanned aerial vehicle, and aims to solve the problem of low detection precision caused by target attitude distortion and insufficient effective information coverage in a multi-view scene of the unmanned aerial vehicle in a traditional target detection technology. According to the method, an unmanned aerial vehicle image data set including multi-height, multi-view and multi-illumination conditions is constructed, and a distortion preserving enhancement strategy is designed to simulate a real shooting environment. In the detection stage, firstly, an initial axis alignment bounding box is extracted, grid units are divided, and the effective information coverage rate is calculated; an optimal rotation angle is dynamically searched through an optimization algorithm, so that the coverage of key features in a target frame is maximized; and finally, a rotated target frame is generated, so that the accuracy and robustness of target detection are remarkably improved. The method is suitable for complex scenes such as unmanned aerial vehicle inspection and security monitoring, can effectively cope with challenges such as view angle inclination and target shielding, and has wide application value.

The invention discloses a network-on-chip debugging method and device, computer equipment and a storage medium, and relates to the technical field of integrated circuit design verification, and the method comprises the steps: generating network-on-chip data files in a preset file format, and generating a network-on-chip database containing network debugging information according to the files; acquiring target information corresponding to the network-on-chip debugging request from a network-on-chip database; and performing on-chip network debugging according to the target information, and writing a debugging result into an on-chip network database. The problem that NoC debugging is low in debugging efficiency and depends on verification of experiences of engineers can be solved. According to the method, the target information corresponding to the debugging request is provided for the user through the network-on-chip database, the dependence on the experience of a verification engineer is eliminated, the network-on-chip debugging difficulty is reduced, and the debugging efficiency is improved. All possible communication scenes and boundary conditions in the debugging process are covered through the target information, and the debugging coverage rate is increased. And continuously improving the database according to the debugging result to form knowledge resources.

The invention discloses a long text abstract generation method based on hierarchical graph comparison themes, which comprises the following steps of: 1, preprocessing an original document, dividing sentence sequences, and obtaining global context-aware sentence and document representation through a hierarchical encoder network; 2, deducing document-level and sentence-level topic distribution by using a neural topic model; and 3, constructing a supervision graph based on a standard abstract to perform graph comparison learning so as to close the topic representation of a document and a key sentence and push redundant information. According to the method, the deep semantic structure of the long document can be effectively captured, so that the theme consistency and the information coverage degree of the abstract can be improved, and the redundancy is reduced.

The application discloses a kind of multi-document abstract generation methods based on key event, first by internet collection under the same theme multiple media articles, and in document set basis, according to artificial rule, standard abstract is generated to construct sample dataset;Then the dataset is preprocessed, and the input data of training model is generated;Then construct the sequence-to-sequence multi-document abstract generation model based on key event fusion;Finally, based on the model after training, the output model is constructed, and the document set to be summarized is automatically summarized using the output model.The application uses event extraction technology to extract key events containing dynamic and static information from multiple documents to mine the relationship of multiple documents, which can guide the abstract generation process at multiple levels, thereby improving the information coverage and factual consistency of the abstract result, highlighting the event information in the original text, and enhancing the logicality of the abstract.

The utility model discloses an anti-static protection device for oil loading and unloading of an oil tank truck, which belongs to the technical field of oil loading and unloading protection devices and comprises a support rod, a detection component is fixedly connected to the side surface of the support rod and comprises a touch screen, and one side of the touch screen is electrically connected with an electrostatic sensor. And the electrostatic sensor is fixedly connected to the side face of the supporting rod, the other side of the touch screen is electrically connected with a broadcasting sound box, and the broadcasting sound box is fixedly connected to the side face of the supporting rod. According to the anti-static protection device for oil loading and unloading of the oil tank truck, static electricity is sensed through the static electricity sensor and transmitted to the touch screen to be displayed, a detection numerical value is broadcasted through the broadcasting loudspeaker, and therefore under the condition that the sight of an operator cannot focus on the screen all the time, the newest static electricity detection numerical value can be obtained at the first time through an auditory channel; omnibearing and dead-corner-free electrostatic monitoring information coverage is really achieved, and powerful support is provided for taking anti-static measures in time and guaranteeing operation safety.

The invention provides a literature report generation evaluation method and system based on a large model, and the method comprises the steps: obtaining a literature image data set containing non-text elements, and the non-text elements comprise chart elements and formula symbols; the method comprises the following steps: separating different spectral band data of a literature image data set to generate multi-channel spectral data containing color distribution characteristics and material reflection characteristics, and dividing a high-sensitivity band and a low-sensitivity band of the multi-channel spectral data according to a spectral sensitivity threshold, calculating spectral characteristic difference quantity between the two wave bands and executing bit width distribution to generate spatial continuity coded data and frequency domain distribution coded data; analyzing the two types of coded data through a large model to generate a structured text description, and verifying the information coverage degree of the description relative to the literature image data set to generate an evaluation result; according to the method, the recognition precision and the structural description capability of the non-text elements in the document image are improved, and the requirements of automatic analysis and evaluation of high-quality multimedia documents are met.

The invention provides a noise-induced hearing loss genetic risk prediction method and system, and relates to the technical field of gene detection.The method comprises the steps that a gene Panel is constructed based on noise-induced hearing loss genome data, a sample is sequenced through the gene Panel, and a sequencing result is obtained; performing linkage imbalance pruning on a sequencing result to obtain SNPs (Single Nucleotide Polymorphisms); carrying out dimensionality reduction on the SNPs based on principal component analysis to obtain a plurality of principal component data; and calculating to obtain a polygene risk score, synchronizing the polygene risk score and the plurality of principal component data to the noise-induced hearing loss prediction model for analysis, and determining a genetic risk prediction report. The technical problem that in the prior art, due to the fact that genetic risk prediction research only pays attention to a small number of genes and the information coverage degree is low, the accuracy and applicability of the prediction result are insufficient is solved, the prediction accuracy, stability and generalization ability are improved, and therefore the technical effect of individualized noise-induced hearing loss risk assessment is achieved.

A single-cell level spatial omics multi-modal fusion method, comprising: extracting differential expression genes and nuclear spatial morphological features from spatial transcriptome data, single-cell sequencing data and histological images, and realizing field adaptation between different platforms by using conditional variational autoencoder. Based on a probability inference model, spatial transcriptome expression, single-cell omics and morphological features are fused to jointly infer the type and gene expression level of each cell. A spatial cell network is constructed by a graph attention mechanism to realize the spatial diffusion and recognition of cell types in the whole slice range. Combined with a multi-omics enhancement module, the unmeasured gene and protein expression are completed based on expression similarity, and the prediction consistency is improved through spatial correction. The method realizes high-resolution reconstruction of single-cell multi-omics information in three-dimensional space, improves the information coverage and spatial resolution of spatial omics data, and provides an efficient and low-cost solution for spatial biology and precision medicine research.

The application relates to a chip verification method, device, equipment, storage medium and program product. The method comprises the following steps: acquiring a simulation log file and an instruction information file of a chip; matching first instruction information and second instruction information; and performing coverage verification on the instruction information file according to a matching result. The first instruction information actually executed by the chip in a simulation verification process is recorded in the simulation log file, the second instruction information required to be executed by the chip in a starting stage is contained in the instruction information file, and the coverage verification is used for verifying a coverage degree of the instruction information file by the simulation log file. In the method, the dynamic execution track of the chip in the simulation verification process can be matched with the static instruction required in the starting stage by acquiring the simulation log file and the instruction information file, the instructions actually executed in simulation and not actually executed in simulation in the instruction information file can be quickly identified, and the chip verification efficiency and accuracy are improved.

The invention relates to the technical field of data processing, in particular to an import and export dangerous chemical intelligent analysis method based on machine learning, and the method comprises the steps: constructing a dangerous chemical knowledge graph, and carrying out the path detection of the dangerous chemical knowledge graph, and obtaining at least one effective path and at least one invalid path; for any invalid path, obtaining a value index of any invalid path according to the information coverage degree between the intermediate entities of any invalid path, the similarity characteristics between the adjacent intermediate entities of any invalid path and the reliability degree of each connection segment in any invalid path; and screening at least one high-value path from all the invalid paths by using the value index of each invalid path, and performing feature extraction and model training on all the high-value paths and all the effective paths by using a PRA path ranking algorithm to obtain a dangerous chemical analysis model. The method is used for comprehensively and accurately deducing similar substances or substitutes of dangerous chemicals.

The invention discloses an intelligent multimedia man-machine interaction system, and relates to the man-machine interaction field, the intelligent multimedia man-machine interaction system comprises an interaction rocking bar and a feedback platform, the interaction rocking bar is in signal connection with the feedback platform, the top of the interaction rocking bar is provided with a control button, and the feedback platform uses an information display system. Comprising an information compression module, an information display module and a custom module, and the information compression module uses a lossy compression algorithm to store multimedia information. According to the method, the keywords are analyzed according to the input content, the corresponding information is retrieved in the multimedia database according to the keywords, the effect of improving the accuracy of retrieved data is achieved, the error range is reduced, meanwhile, the framework layer establishes the relation between the keywords and the multimedia information and builds an information framework, and the information framework is more accurate. The information retrieved according to the keyword covers an information frame established according to the multimedia information to form a main interface and an auxiliary interface, and the main interface and the auxiliary interface are displayed on a feedback platform after being processed by a display layer.

The present invention discloses a method and system for monitoring and warning of on-orbit anomalies of remote sensing satellite instruments, wherein the method comprises: collecting and acquiring on-orbit operation data of remote sensing satellite instruments; presetting parameter thresholds and trend thresholds of instrument telemetry parameter data; generating telemetry anomaly alarm information; presetting data integrity constraints and business process constraints of instrument remote sensing business data; generating remote sensing anomaly alarm information; performing multi-source alarm information matching on telemetry anomaly alarm information and remote sensing anomaly alarm information, generating composite anomaly alarm information based on the matching results; and performing feedback optimization based on the composite anomaly alarm information. The method solves the technical problems of incomplete alarm information, easy omission or false alarm, and low accuracy and reliability of anomaly monitoring in existing remote sensing satellite instrument anomaly monitoring, thereby achieving the technical effects of improving the information coverage of instrument anomaly alarms, reducing omissions and false alarms of alarm information, and improving the accuracy and reliability of anomaly monitoring.

The application discloses a data acquisition method and device, electronic equipment and storage medium. The method comprises: acquiring audio to be processed collected through a microphone array, the audio to be processed comprising multiple sentences of multi-channel audio; for each sentence of multi-channel audio, acquiring a phase difference feature between at least one group of specified channel audio as target data, the specified channel audio comprising at least two position-associated channel audios. For each sentence of multi-channel audio, the method performs phase difference calculation by incorporating the audio of at least two position-associated microphone channels, which can generate higher-dimensional phase information coverage on one hand, so that the DOA feature obtained after phase difference is more intensive, thereby helping to improve the accuracy of the DOA encoding result; on the other hand, since the position-associated microphone channel audio is used for phase difference calculation, data redundancy can be avoided, thereby helping to improve the efficiency of DOA encoding.

The present invention discloses a method for optimizing the deployment of rechargeable Internet of Things nodes based on trusted information coverage: a network model is constructed by combining environmental energy distribution and trusted information coverage; an integer linear programming rechargeable Internet of Things node optimization deployment model is constructed by taking environmental correlation into consideration using the constructed network model; and the proposed node optimization deployment model is solved using greedy and approximation methods. In the scenario of the rechargeable Internet of Things, the present invention mines environmental correlation from the perspective of information collaborative perception, combines energy distribution, and uses Kriging interpolation and root mean square error to estimate coverage error, rationally utilizes energy, and effectively reduces deployment costs; adopts greedy thinking and combines binomial methods to solve integer linear programming models in large-scale scenarios, with fast solution speed and high accuracy, high approximation ratio and high efficiency; the method is applicable to a variety of application scenarios, trusted information coverage model, and is applicable to coverage and deployment in different environments, weather, and terrains.