374 results about "Mapping system" patented technology

The invention discloses a vehicle-mounted cross-protocol data time sequence cooperative processing method, which comprises the following steps: establishing a unified time reference, and providing an accurate space-time coordinate system for heterogeneous network nodes by electing a global master clock and constructing a clock relation model and a periodic correction mechanism; systematic cognition and management of communication resources are realized, and a verified protocol capability table is generated by automatically identifying protocol types and variants; constructing an automatic mapping system from demand to execution, performing formalized packaging on a target scene by introducing a unified intermediate model, generating a cross-protocol mapping rule based on the model and a protocol capability table, and then forming a global scheduling table in combination with a unified time reference; the cooperative communication of all nodes is finally realized by using the global scheduling table, and the end-to-end delay is constrained within the preset range, so that the problem that the end-to-end time sequence in the vehicle-mounted heterogeneous network is uncontrollable is solved, and the controllability and reliability of the time sequence of the vehicle-mounted network are improved.

A swimmer emergency alerting, tracking, rescue assistance, and rip current mapping system includes a stand and a life preserver that is removably mounted to the stand. The stand includes a solar panel or other charger, and the life preserver includes a battery receiving power from the charger and a sensor that is driven by the battery, such as to detect a location of the life preserver. The stand and the life preservers may wirelessly communicate with another device, such as a user device, to provide information on a status of the stand and the life preserver. A drone may fly from the stand and collect images of a shore, and the drone may process the images to identify a rip current. The drone may use data from a watercraft identifying rip current to train the processing of the images.

The invention relates to the technical field of unmanned aerial vehicle cooperative surveying and mapping, and discloses an unmanned aerial vehicle cluster cooperative space-space-ground integrated surveying and mapping system which comprises a space-time reference construction module, a multi-source data acquisition module, a distributed fusion optimization module, a system adaptive reconstruction module and a four-dimensional model generation module. An internal high-precision space-time reference independent of the GNSS is constructed; uniformly modeling the whole surveying and mapping task into a space-time factor graph through a distributed fusion optimization module, and solving the space-time factor graph; and closed-loop adaptive adjustment is performed on the geometric configuration of the beacon network and the measurement data quality through a system adaptive reconstruction module. The technical problem that a traditional surveying and mapping system is poor in precision and reliability in a GNSS disturbed environment is solved, the robustness, autonomy and environment adaptability of the system are remarkably improved by constructing a self-consistent internal reference and introducing intelligent feedback control, and a globally consistent high-precision four-dimensional space-time model can be efficiently generated.

The invention discloses an intelligent surveying and mapping system for catenary equipment in a tunnel, which relates to the technical field of catenary engineering detection and comprises a multi-source data acquisition module, a multi-source data fusion module, an identification and parameter calculation module, a modeling and interaction module and a data management and application output module. According to the invention, by deploying the multi-dimensional sensor, the limitation of traditional manual inspection or dependence of a single sensor is broken through aiming at the environments of insufficient illumination, high dust concentration and the like in the tunnel, the laser scanner can penetrate through the dust to obtain the three-dimensional geometric framework of the equipment, and the Beidou positioning assembly is bound with the collection action in real time; the problem of positioning deviation caused by weak GPS signals in the tunnel is solved, the environment sensor group monitors parameters such as temperature, humidity and illumination in real time, and through a dynamic adaptation fusion coefficient formula, sensor data weight is calculated, original coordinate deviation is corrected, a four-dimensional fusion data set is constructed, and errors caused by environment interference or data isolation in a traditional method are solved.

The invention belongs to the field of data processing, particularly relates to a wind turbine generator gear box tooth surface strength optimization method considering multi-working-condition load distribution, and aims to solve the problem that the optimization effect is affected due to the fact that strength optimization checking is carried out only for a single working condition in the prior art. The method comprises the following steps: acquiring working condition data of the gearbox under various preset working conditions; load spectrum decoupling processing is conducted on the working condition data, a dynamic load distribution matrix synchronous with the tooth surface meshing period is determined, stress field conversion is conducted on the dynamic load distribution matrix, and a tooth root bending stress field and a tooth surface contact stress field are obtained; inputting the tooth root bending stress field and the tooth surface contact stress field into a pre-constructed double-constraint optimization model to obtain a tooth surface strengthening parameter tensor output by the model; and inputting the tooth surface strengthening parameter tensor into a preset process mapping system. Based on the method provided by the invention, the multi-working-condition operation data of the gearbox are synchronously obtained for optimization calculation, and the limitation of traditional single load analysis is broken through.

The invention discloses a building surveying and mapping system based on an unmanned aerial vehicle remote sensing technology, and belongs to the technical field of building surveying and mapping. Comprising the following modules: a multi-sensor data acquisition module and an unmanned aerial vehicle data acquisition platform based on an integrated RGB camera, a laser radar and a multi-spectral sensor; the preliminary image processing module is used for generating standardized image data for scene analysis; the intelligent scene recognition module outputs a scene classification result and preliminary complexity grade evaluation; the self-adaptive decision module is used for generating an initial image processing parameter combination according to a scene recognition result; the dynamic image processing module is used for executing regional image registration, correction and seamless splicing based on the initial parameter combination to generate a building orthoimage; and the real-time quality evaluation module monitors and evaluates geometric accuracy and visual quality in the image processing process in real time.

The invention discloses an SLAM front-end optimization method based on brightness grading and gradient constraint, and relates to the technical field of computer vision and vision SLAM. In order to solve the defects that adaptive grading enhancement and parameterization control based on illumination types are lacked in the prior art, and feature point quality, spatial distribution uniformity and front-end real-time performance are difficult to consider in a high-frequency input scene, the invention provides a comprehensive brightness grading and feature optimization scheme. The method comprises the following steps: firstly, calculating the average brightness of an input image, dividing the image into a dark light type, a normal type and an overexposure type, and respectively adopting gamma correction, contrast limited adaptive histogram equalization and inversion enhancement strategies for different types to realize illumination adaptive enhancement; then screening high-quality feature points with significant local curvature changes; and updating the detection area. According to the method, the feature stability, the matching precision and the real-time performance of the SLAM front end in a complex indoor environment are remarkably improved, and the method is suitable for a self-localization and mapping system.

The invention discloses a semantic matching-based field name standard abbreviation mapping method and system, and particularly relates to the technical field of data governance, a source field set to be subjected to abbreviation and a standard field set in a standard field library are acquired, field names and field descriptions are normalized, and field text representation is generated; using the pre-training language model to generate a semantic vector and recalling a candidate mapping pair set; calculating character string similarity, synonym expansion matching score, data type consistency score and sample value pattern consistency score for the candidate mapping pairs; generating a neighbor confusion risk index based on semantic neighbor density, entity category distribution deviation, synonym expansion and context anti-verification, performing risk gating correction, and judging a score in combination with a difficult case; and applying table-level consistency constraints in the same service table or entity domain to carry out joint consistency solution to obtain a table-level optimal mapping scheme, generating confirmation confidence, and outputting an automatic confirmation or manual recheck mapping result.

The invention discloses a spatial deformation analysis method and system based on unmanned aerial vehicle surveying and mapping and a set unmanned aerial vehicle surveying and mapping system, and the system comprises a data acquisition module S1, a preprocessing module S2, a deformation analysis engine S3, a visual early warning module S4, a report generation module S5 and a system management module S6. Space reference precise transmission, error space distribution modeling, multi-source data space fusion and cross-scale three-dimensional field construction are realized, and'dynamic environment anti-interference 'and'error space-time propagation control' are broken through, so that all-weather credible perception of geologic body millimeter-level deformation is realized. According to the spatial deformation analysis method and system based on unmanned aerial vehicle surveying and mapping, through triple optimization of multi-source sensing fusion, error spatial modeling and a self-adaptive algorithm, the defects of traditional unmanned aerial vehicle deformation monitoring in the aspects of complex environment adaptability, precision reliability and automation degree are overcome, a long-time-sequence error propagation model and edge calculation acceleration are broken through, and the method and the system have good application prospects. Therefore, millimeter-level near-real-time early warning of geological safety risks is realized.

A guidance system for efficiently providing a mapped path for a shopper in a store. The guidance system including one or more processors and one or more tangible, non-transitory, computer-readable media storing instructions, wherein the instructions, when executed by the one or more processors, cause the guidance system to analyze data indicative of a plurality of purchase items, map each purchase item of the plurality of purchase items to a respective purchase item location in a store to provide a mapping of the plurality of purchase items, determine a route through the store based on the mapping of the plurality of purchase items such that the route includes the respective purchase item locations, and provide a display of the route including a graphical indication of each of the respective purchase item locations via a graphical user interface of a computing device.

The invention relates to the technical field of electric power system operation and control, and discloses a system-perspective networking capability evaluation index and power supply parameter mapping system, which comprises a data acquisition module, a dynamic tensor modeling module, a coupling decomposition module, a distributed optimization module, an index fusion module and an edge cloud collaboration module. The method comprises the steps of constructing a dynamic tensor by collecting power grid data in real time, decomposing and extracting coupling features and generating optimization constraints, realizing parameter cooperative adjustment based on hierarchical multi-objective optimization and quantum particle swarm optimization, and forming a closed-loop optimization process by combining entropy weight-TOPSIS weight distribution and edge federated learning feedback updating. According to the method, the time-space correlation characteristics of the power grid are extracted by improving Tucker tensor decomposition, hierarchical ADMM optimization and quantum particle swarm optimization are combined, an entropy weight-TOPSIS dynamic weighting and federated edge collaboration mechanism is adopted, a power supply parameter-network construction capability index mapping model is constructed, and the multi-target optimization precision, the real-time performance and the data privacy are improved.

The invention relates to the field of surveying and mapping, in particular to a laser-IMU (Inertial Measurement Unit) installation deviation calibration method based on vision assistance, a surveying and mapping method and a surveying and mapping system, a plurality of images under a plurality of laser radar calibration conditions are processed according to camera parameters and camera-IMU associated parameters, laser radar-IMU installation deviation is obtained, manual operation is avoided, and high-precision and high-efficiency deviation calibration is realized; in addition, according to the installation deviation of the laser radar-IMU, the relative space relation of the laser radar-IMU is adjusted, and accurate matching installation of the laser radar and the IMU is ensured; and according to the dynamic characteristics of the surveying and mapping path, constructing a corresponding relation between IMU data and point cloud data frames, and screening a point cloud data point which is most matched with the position point of the surveying and mapping path where each IMU data is located so as to construct a local point cloud map corresponding to the position point, thereby integrating and constructing a space map of a target area where the surveying and mapping path is located. According to the method, data omission can be reduced through local point cloud data processing and map construction, and the accuracy and credibility of spatial surveying and mapping positioning are improved.

The invention relates to the technical field of hybrid intelligence, in particular to a quadruped robot motion control and operation system for an industrial environment, which realizes full-link intelligent management from environment perception to motion control, and remarkably improves the operation precision of a robot and the system efficiency. A three-dimensional map is constructed through a multi-sensor fused environment sensing module, and precise positioning is realized by combining state estimation based on deep learning; a motion control module with a hierarchical control architecture is adopted, and stable motion under a complex terrain is ensured through model prediction and gait optimization; the digital twinning and cloud side end collaboratively constructs a virtual-real mapping system to realize predictive maintenance and remote monitoring; and the multi-agent coordination module realizes task coordination and resource optimization of the multi-robot system through a distributed scheduling algorithm.

System and method for lidar-based anatomical mapping is provided. In one implementation, a LIDAR imaging technology is utilized to create a surface-based anatomical map of an exposed anatomical surface of at least a portion of the spine, or other anatomical features, using anatomical and / or artificial landmarks are disclosed. The surface mapping can then be registered with previously acquired images of at least the portion of the spine, or other anatomical features. The surface mapping can then be used to identify important structures, including an entry point in tissue (including soft tissue and bone) for the placement of a medical instrument or implant, or for Information the orientation of a medical instrument or device. The information can be displayed in an augmented reality overlay on a device display (e.g., wearable eyeglasses). The LIDAR imaging technology may be incorporated into wearable eyeglasses.

The invention provides an unmanned vehicle local high-precision positioning mapping system and method based on reinforcement learning polarization normal deambiguity and depth information fusion, and the method comprises the steps: synchronously obtaining a polarization image and a depth image of a target scene in the driving process of an unmanned vehicle in a low-texture and low-illumination scene; constructing the polarization normal candidate, the depth normal, the neighborhood surface curvature and the depth gradient information into a state vector, inputting the state vector into a reinforcement learning agent based on Dueling DQN, and obtaining the depth gradient according to a reward function fusing the included angle error of the polarization normal and the depth normal, the neighborhood normal smoothness loss and the consistency error of the polarization normal and the depth gradient direction. Outputting an optimal polarization normal selection action to obtain an unambiguous surface normal; polarization estimation depths are generated, and confidence coefficients are calculated respectively; according to the depth confidence coefficient and the polarization confidence coefficient, pixel-level weighted fusion is carried out, a fused depth map is obtained, synchronous positioning and mapping are carried out on the fused depth map and the synchronous RGB image, and a point cloud map of the target scene and the moving track of the unmanned vehicle are output.

The invention relates to the technical field of unmanned aerial vehicle surveying and mapping, and discloses a pressure pipeline axonometric mapping system based on an unmanned aerial vehicle, and the system uses a pipeline anchoring relative navigation module to guide the unmanned aerial vehicle to fly along a line with a target pipeline as a reference; the outer diameter and three-dimensional center point coordinates of the pipeline are obtained in real time through an orthogonal contour scanning and parameter resolving module; a self-adaptive flight and measurement control module is used for adjusting the flight distance according to the measured outer diameter feedback, and adjusting sensor parameters according to the imaging quality feedback; meanwhile, the coordinates of the center point are incrementally constructed into a topological graph through an airborne real-time topological graph construction and node processing module, pipe fitting nodes are autonomously detected and recognized, and then a preset strategy is called to conduct refined scanning on the nodes. According to the invention, autonomous navigation independent of global positioning, self-adaptive closed-loop control of measurement and flight, and airborne integrated real-time modeling of pipe network topology and geometric information are realized, and the surveying and mapping precision, the automation level and the operation efficiency are remarkably improved.

The invention discloses a gear machine tool expert system construction method based on a generative rule, and the method comprises the steps: firstly carrying out the multi-dimensional modeling of a gear and a machine tool through an object-oriented technology, enabling a gear model to distinguish the characteristics of an axis position, a tooth curve and the like through an interface, and enabling a machine tool model to distinguish the machining technology and the precision grade through an interface; secondly, establishing a generation type rule mapping system from geometric, precision, material and functional attributes of the gear to machine tool movement, precision, process and rigidity attributes; finally, an intelligent reasoning system including forward reasoning, reverse verification, conflict coordination and self-learning iteration is constructed, and automatic and accurate matching from gear design requirements to machine tool optimization configuration is achieved. According to the method, the problems of high subjectivity and low efficiency caused by dependence on expert experience in the prior art are solved, and knowledge-driven intelligent decision making is realized.

The invention discloses a display equipment brightness dynamic adjusting method and system based on human factor engineering, and belongs to the field of liquid crystal display. Aiming at the problems of human eye perception deviation and visual fatigue caused by the fact that traditional display equipment depends on a fixed Gamma curve, an eye movement tracking module and an ambient light sensor are integrated to collect physiological signals and ambient light parameters of a user in real time, and a brightness perception nonlinear function is constructed in combination with the Weber-Fechner law; and brightness curve parameters are dynamically optimized by using a deep reinforcement learning algorithm, so that environment adaptive adjustment of the Gamma value is realized. According to the method, through real-time fusion of multi-modal physiological signals and environmental data, in combination with a human eye visual perception model and a deep reinforcement learning algorithm, a dynamic self-adaptive brightness mapping system is constructed, and triple breakthrough of visual comfort, energy efficiency and image quality of display equipment in a complex scene is realized on the premise that hardware architecture does not need to be changed.

The invention relates to a mapping system and method for flight inspection of indoor equipment, the system comprises a data acquisition end and an offline data processing end, the data acquisition end comprises an unmanned aerial vehicle and a sensing module, and the sensing module comprises a laser radar module, a binocular camera module, an inertial measurement module and an airborne recording module; the method comprises the following steps: synchronously acquiring multi-source data through layered flight; performing space-time alignment and preprocessing; self-adaptive sampling is carried out based on point cloud geometric prior guide image features, and laser-vision joint features are generated; fusing point cloud registration, joint features and inertial data, and carrying out joint estimation on adjacent frame pose increments; performing loopback detection based on the key frame to generate a closed-loop constraint; constructing and optimizing a pose map to eliminate cumulative drift; and finally fusing to generate a global point cloud map. According to the method, the space consistency and geometric accuracy of the map can be effectively improved, and a reliable data basis is provided for digital modeling and intelligent operation and maintenance of indoor equipment inspection.

The invention discloses a lightweight real-time mapping system based on cloud edge collaboration and a VLA-HDMap high-frequency interaction method, and aims to solve the problems of slow updating, high cost and low safety of HDMap. The model has the capabilities of real-time environment understanding, semantic analysis and end-to-end decision instruction output. The vehicle end can download the cloud HMap in real time, and also participates in crowdsourcing data acquisition and uploading. According to the local lightweight mapping method provided by the invention, a real-time circulation mechanism of'acquisition-application-correction 'is used, so that the HDMap is highly consistent with the actual environment. A cloud edge collaborative hierarchical parallel incremental update global HDMap is also provided, the essence is a time-space intersection multi-scale analysis model of minute-level traffic flow prediction and day / week-level map differentiation detection, a high-risk region of traffic flow peak + map change can be efficiently identified, and a convex hull algorithm is used to obtain a region, which needs to be locally updated, of the whole HDMap. According to the invention, a new-generation intelligent traffic system can be constructed, and the safety application of group intelligence, symbiotic economy and large-scale automatic driving can be promoted.

The invention relates to the technical field of laser ranging, in particular to a novel railway tunnel deformation real-time surveying and mapping system based on a three-dimensional scanning technology, which comprises a laser sampling module, an echo evaluation module, a space repositioning module, a residual evolution module and a deformation surveying and mapping module. According to the method, after continuous distance information of a target position is obtained, measuring point sequence data is constructed based on a time sequence, a signal abnormal area is recognized through echo intensity fluctuation, the signal abnormal area is further converted into a space coordinate structure, track differences are extracted, vector data are generated, deviation characteristics are analyzed in combination with the tunnel space position, and the deformation amplitude is quantified. Compared with a periodic observation mode depending on manual distribution of measuring points, the method has the advantages that fine coordinate difference data can be continuously output, the deformation monitoring frequency and the space coverage range can be improved, manual interference errors can be reduced, and the dynamic mastering capability of the tunnel structure evolution process can be enhanced.

The invention discloses a global-oriented multi-language multi-time-zone power station management method and system, and relates to the technical field of electric power digital management, and the method comprises the steps: collecting power station data, carrying out the standardized identification, and constructing a power station multistage coding identification main key; a multi-language mapping system is constructed by taking a multi-level coding identification main key of a power station as a drive, and time zone offset logic is constructed by using standardized identification; and performing hierarchical authority control based on the power station multi-level coding identification primary key prefix and generating a localized alarm prompt. According to the method, standardized identification of power station data is realized by constructing a unified power station multi-level coding main key; based on primary key driving multi-language mapping and time zone offset processing, accurate presentation and time consistency of data in a multi-language environment are guaranteed; authority control is achieved through primary key prefix division, multi-language alarm prompts are triggered in combination with signal coding, and a power station event management mechanism which is clear in alarm semantics, timely in response and controllable in boundary is achieved.

Examples include techniques associated with mapping system memory physical addresses to isolation domains for uniform memory access (UMA) by a system. Examples include mapping separate system memory physical addresses ranges associated with memory devices communicatively coupled with at least one compute die of the system through an input / output (I / O) die of the system. The separate system memory physical addresses to be mapped to isolation domains and address decoder information is generated to indicate the mapping of the separate system memory physical address ranges to the isolation domains.

The invention provides an intelligent gridding comprehensive anti-misoperation locking system for a power distribution network, and the system comprises an optimization module which achieves the hierarchical decoupling design of the system through a distributed communication middle platform, an intelligent logic analysis engine and a programmable execution control unit. The deployment module is used for modularly deploying functional components based on the micro-service architecture, reducing the system coupling degree by using an asynchronous message queue as a cross-component communication bus in combination with a domain event-driven mechanism, and completing local logic judgment at an edge computing node through an FPGA (Field Programmable Gate Array); the network reinforcement module is used for constructing a heterogeneous communication network and guaranteeing the communication quality through a dual-channel redundancy transmission technology; the intelligent decision-making module is used for forming a self-adaptive decision-making model based on reinforcement learning and a knowledge graph technology; and the digital twinning verification module is used for establishing a power grid virtual mapping system through a digital twinning technology. Cooperation among modules of the system can be balanced, instruction processing time delay is shortened, communication reliability is improved, and efficient implementation of an operation scheme is guaranteed.

The invention belongs to the technical field of surveying and mapping remote sensing, and discloses an automatic surveying and mapping system and method for urban and rural planning complex terrains based on image analysis. The method comprises the following steps of: acquiring multi-view heterogeneous image data of a target surveying and mapping area, performing layered decoupling processing and multi-view registration on an image, identifying spectral texture features and geometric three-dimensional features of a terrain, and performing complexity function partitioning on the surveying and mapping area according to the spectral texture features and the geometric three-dimensional features; the regional surveying and mapping demand degree is calculated by analyzing a terrain local complexity index and spatial distribution dispersion characteristics, so that a personalized sampling parameter range is screened out; constructing an optimized three-dimensional terrain model by fusing a terrain feature map, a point cloud reconstruction result and a geometric constraint attribute, predicting surveying and mapping precision, and performing comparative analysis on the predicted surveying and mapping precision and a back projection result to obtain a confidence evaluation result; the method is applied to a personalized urban and rural planning surveying and mapping scheme; according to the invention, accurate identification and personalized automatic surveying and mapping of the complex terrain are realized.

The invention discloses a regional supply chain planning surveying and mapping system and surveying and mapping method based on an unmanned aerial vehicle, and relates to the technical field of planning analysis, and the method comprises the steps: carrying out the supply chain network connectivity evaluation and path optimization analysis of supply chain infrastructure data, and obtaining supply chain network connectivity data and path optimization data; carrying out storage position rationality evaluation and transportation efficiency analysis to obtain storage position rationality data and transportation efficiency data; performing supply chain planning strategy generation on the supply chain infrastructure data to obtain supply chain planning strategy data, and performing adjustment learning based on the supply chain planning strategy data to obtain a dynamic supply chain adjustment logic strategy; and performing execution unit design on the dynamic supply chain adjustment logic strategy to obtain a supply chain planning automation unit, and embedding the supply chain planning automation unit into the regional supply chain management system to execute the regional supply chain planning surveying and mapping method. The method has the effect of improving the supply chain planning surveying and mapping efficiency.

The invention relates to the technical field of disaster site surveying and mapping, and discloses a disaster site three-dimensional surveying and mapping system based on an unmanned aerial vehicle. According to the system, an unmanned aerial vehicle is controlled to carry a multispectral sensor to carry out omnibearing scanning on a disaster site, and earth surface deformation data and multiband reflectivity data are collected; carrying out time sequence alignment and noise filtering on the collected data, constructing an initial three-dimensional point cloud through dynamic voxelization processing, and fusing inertial measurement unit data to correct a spatial position; identifying earth surface fault zone edge and elevation mutation features from the point cloud, and dividing geological stability partitions by combining reflectivity data; a self-adaptive octree segmentation algorithm is adopted to carry out multi-level detail division on the stability partitions, the grid resolution is automatically adjusted according to the fault zone density, and a disaster site three-dimensional topological structure is generated; by comparing historical and current three-dimensional data, the earth surface displacement vector and the settlement gradient are calculated, a potential secondary disaster risk area is marked, and accurate assessment and risk early warning of a disaster site are achieved.

The invention discloses a real estate surveying and mapping system and method based on a geographic information system, and the system comprises an unmanned aerial vehicle surveying and mapping unit which is responsible for the collection of large-range images and laser point clouds in the air, and carries out the self-adaptive adjustment of measurement parameters according to the type of real estate. The laser measurement unit correspondingly completes measurement and supplementary measurement of a ground high-precision boundary point and can identify a shielding object in a measurement path and trigger a supplementary measurement signal, and the positioning enhancement unit provides anti-interference multi-source positioning support for the whole system so as to ensure continuous stability of positioning in a complex environment. The data fusion calibration unit unifies coordinates of cross-medium data, synchronizes timestamps and corrects data fusion deviation, the GIS processing unit undertakes core tasks of geographic information management, data processing and surveying and mapping result generation, and the linkage verification unit realizes real-time linkage verification of surveying and mapping data and real estate registration data and identifies ownership boundary conflicts. The system has the advantages of multi-source cooperation, self-adaptive matching, enhanced anti-interference and linkage calibration.

The invention relates to the technical field of map data formatting, in particular to a multi-source data fused geological information intelligent surveying and mapping system, which comprises a geological element objectification packaging module, a geological element mapping module, a geological element mapping module, a geological element mapping module, a geological element mapping module, a geological element mapping module, a geological element mapping module, a geological element mapping module, a geological element mapping module and a geological element mapping module, and synchronously obtaining the ID, the timestamp and the data source metadata of each element, and generating a unified geological object set with an identifier. According to the method, objectification integration is carried out on multi-source geological data, and interoperability and traceability are enhanced; a topological relation is internally borne, so that high efficiency of spatial operation and data retrieval is realized; through fine control and encryption of attribute fields and combination of packaging and watermarking technologies, a tamper-proof and traceable closed-loop security guarantee system is constructed, the credibility and integrity of data are improved, and a comprehensive guarantee from generation to verification is formed.

Some embodiments provide systems to control customized retail product performance information, comprising: a linkage mapping system to define and update linkings within a knowledge graph; a personalization recommendation system controlling different display systems to control graphical user interfaces presenting customized anomaly notification information specific to intended recipients as a function of the linkings; and a community detection system applying a set of machine learning community detection models to identify additional relationships between two or more of the entity nodes, based on feedback data from multiple intended recipients, and cause the linkage mapping system to update the multi-level linkages to embed one or more additional association links between the two or more of the entity nodes; wherein the personalization recommendation system is configured to control, based on the updated additional association links, a first graphical user interface to present first customized anomaly notification information specific to a first intended recipient.