135 results about "Central database" patented technology

The invention relates to the technical field of landscape evaluation, and discloses an urban green land landscape evaluation method based on a large model, and the method comprises the steps: carrying out the real-time analysis and standardization processing of a streetscape image, IoT environment data, satellite vegetation coverage data and RTK high-precision positioning information of a target city district, extracting core landscape elements, building cross-scene semantic mapping, and carrying out the calculation of the cross-scene semantic mapping. Transmitting the standardized data to a central database and deploying edge nodes; extracting a multi-dimensional landscape index by adopting an improved semantic segmentation model, dynamically adjusting an index weight in combination with regional features and seasonal changes, and classifying and correcting deviation data by edge nodes; a visual evaluation result is generated based on a cooperative computing architecture and a digital twinborn model, a landscape space to be promoted is identified, and optimization suggestions are generated; and obtaining planner feedback information, updating the model, the weight rule and the suggestion generation strategy, and forming a closed loop iteration mechanism. According to the method, the dynamic and practical evaluation requirements of the current urban green land landscape can be met.

The invention relates to the technical field of space governance, and discloses a multi-agent space collaborative governance method which comprises the following steps: processing multi-source heterogeneous data such as satellite images and sensor readings, establishing cross-type semantic association through a geographic space data embedding technology, generating a unified structured text after optimizing the satellite images through vLLM, and synchronizing the unified structured text to a central database; an agent role portrait is dynamically generated by the central server large language model based on a preset Prompt template, and generation does not depend on a fixed rule; then, selecting a target node in the edge-center architecture, disassembling a total task into sub-tasks, establishing semantic mapping, calculating a matching probability, and performing optimal distribution by a reward borrowing function; generating a governance scheme in a perception layer-decision layer-execution layer framework, and outputting a coded operation instruction; based on an execution feedback updating strategy, a multi-level mechanism is set, roles are automatically redistributed, and the governance continuity is guaranteed. According to the invention, the overall efficiency and reliability of space governance can be improved in the face of dynamic scenes or emergency situations.

The invention belongs to the technical field of trajectory planning, and provides an electric shovel unmanned mining method and system based on digital twinning in order to solve the problem that the design of an electric shovel unmanned mining trajectory is difficult to deal with a complex heap surface, and the method comprises the following steps: obtaining sensing data, a historical mining trajectory and historical heap surface point cloud data; an electric shovel unmanned mining digital twin system is constructed based on the sensing data; uploading the historical mining trajectory and the historical heap surface point cloud data to a central database, and training by using generative artificial intelligence to obtain prediction trajectories suitable for different mine fields; constructing an agent model by using a neural network, calculating to obtain a predicted fullness rate, and performing simulated excavation according to the predicted fullness rate and the predicted trajectory to obtain electric shovel excavation control data; according to the method, deep reinforcement learning is utilized, the electric shovel unmanned excavation track is generated based on the electric shovel excavation control data, the electric shovel is controlled to conduct unmanned excavation in real time, the safety of the excavation process is guaranteed, and the track control precision of the electric shovel is also improved.

The invention provides an intelligent progress management and control method and system for information engineering supervision, and relates to the technical field of information, and the method comprises the steps: pushing early warning information to a first-party system and a second-party system through message middleware, collecting a feedback state to complete closed-loop cooperative processing, and updating a processing result to a central database; based on the central database, combining historical project data, performing pattern recognition analysis to extract a progress deviation rule, and dynamically optimizing a plan node threshold and buffer time of a subsequent stage according to the progress deviation rule to obtain an optimization strategy; and on the basis of the optimization strategy, constructing a configurable progress management and control template library, so as to quickly adapt and generate a corresponding progress management and control node and an early warning threshold value in the new-type project. According to the invention, a full-process closed-loop management system from data integration, intelligent optimization to dynamic adaptation is constructed, and the fundamental transformation of project progress management and control from passive response to active prediction and from experience driving to data driving is realized.

The invention discloses a chronic disease screening return visit method and system, and relates to the technical field of health management, and the method comprises the steps: obtaining the basic information of a to-be-screened person, and constructing a screening file; generating a screening voucher containing an identity label; parallel data acquisition posts are set, personnel hold vouchers to autonomously select posts, and the posts scan identification associated archives and input multi-dimensional data to a central database in real time to form an associated data set; when the data set contains a preset basic data item, calling a risk scoring model to calculate a chronic disease risk score; and generating a differential detection strategy based on a comparison result of the score and a preset threshold value. According to the method, through parallel post setting and data real-time integration, the problems of post congestion and low efficiency of data integration in a traditional screening process are solved, intelligent risk assessment and detection strategy distribution of to-be-screened personnel are realized, the chronic disease screening efficiency and the resource utilization rate are improved, and a systematized data management scheme is provided for early prevention and control of chronic diseases.

A central database system trains and applies machine-learned models based on characteristics of one or more entities associated with the central database system. For instance, the central database system trains a machine-learned model configured to identify issues a target entity is likely to encounter based on training data identifying characteristics of historical entities and issues faced by the historical entities. Likewise, the central database system trains machine-learned models configured to predict actions that entities are likely to take in the future, and resources required to take those actions. The central database system can then perform one or more proactive actions or make one or more recommendations based on the predicted issues, the predicted future actions, and the predicted required resources.

The invention discloses a concrete material strength detection and analysis system, and relates to the technical field of constructional engineering quality detection. The system comprises a data acquisition module, a data preprocessing module, a fusion and analysis module, a fusion and analysis module and a visual report generation module. Wherein the data acquisition module is used for acquiring multi-source original data of concrete strength; the data preprocessing module is used for performing cleaning, format standardization and invalid value elimination operation on the multi-source original data and storing the multi-source original data in the central database; the fusion and analysis module is used for carrying out strength prediction in future time by adopting a dual-mode comparison prediction method, and sending warning information to detection personnel when a strength prediction value exceeds a prediction threshold value; and the visual report generation module is used for automatically generating a detection report and an analysis chart conforming to a standard format. According to the method, the analysis and evaluation of the concrete strength can be realized by fusing the multi-source detection data and the process data and utilizing a machine learning algorithm.

The invention discloses an intelligent fire-fighting resource dynamic scheduling method based on the Internet of Things, and relates to the technical field of fire-fighting emergency intelligent scheduling, and the method comprises the steps: collecting fire-fighting global situation awareness data, synchronizing the data to a central database through an encryption protocol, and constructing a fire-fighting real-time commanding combat information system; based on a combat information system of fire-fighting real-time commanding, a combat guarantee scheme is formulated, meanwhile, fire-fighting power information, geographical and meteorological information and field real-time information are collected, and a dynamic dispatching instruction is generated; dynamically mapping the dynamic scheduling instruction to a fire-fighting resource state, generating a resource state mapping table, optimizing resource allocation through a resource priority scoring function and a linear programming model, and generating a resource scheduling scheme; performing Bayesian verification and rating processing on professional pointing information in execution of the resource scheduling scheme to generate a targeted action instruction; according to the method, the continuous evolution capability of the scheduling model is realized through a multi-agent voxel learning parameter adjustment framework of the empirical rule base.

The invention provides an unmanned workshop automatic control method based on B / S architecture, which is used in the field of new energy battery detection, and comprises the following steps: S1, a laboratory information management system LIMS initiates a test task request; by integrating a laboratory information management system LIMS, a warehouse management system WMS, an AGV scheduling system, an equipment control system and a central database, a unified and collaborative intelligent management and control system is constructed, and full-process automatic and intelligent management from test task initiation, arrangement and distribution test, battery cell placement, AGV carrying, test execution to final ex-warehouse verification is realized. The bottleneck of a traditional system is broken through from multiple dimensions, and the new energy battery detection process is comprehensively promoted to be transformed and upgraded to be intelligent and unmanned. The battery cell information is automatically identified through code scanning, the corresponding process parameters and the test storage location are matched in a linkage mode, the detection task is intelligently generated, a traditional mode of manual instruction issuing and manual resource allocation is replaced, the labor cost is reduced, and the task processing accuracy and execution efficiency are improved.

The invention discloses a PCB production monitoring method based on the industrial internet and a related device. The method comprises the following steps: deploying a two-dimensional code identifier of a PCB product, installing a plurality of cameras and a plurality of acquisition units to acquire a two-dimensional code picture and environment information of PCB production, and installing a 5G gateway of PLC equipment to transmit the running state of the equipment in real time; on the basis of a 5G network and a wireless sensing technology, the two-dimensional code picture, the operation state and the environment information are preprocessed and uploaded to a central database; performing data association processing on the two-dimensional code picture, the operation state and the environment information through a central database; and when detecting that the produced PCB has a quality problem, calling the information of the corresponding two-dimensional code picture, the operation state and the environment information from the central database, and carrying out quality traceability analysis to generate a quality traceability strategy. According to the invention, accurate monitoring and quality tracing of the PCB production process are realized, so that the intelligent level and the product quality of an enterprise are improved.

The invention provides a soil ecological environment monitoring and management method based on big data, and relates to the technical field of soil ecological environment monitoring and management. According to the method, multi-source data including soil and pasture are collected and integrated to construct a central database through field stratified sampling, classified deployment of sensors and butt joint with a third-party mechanism; space-time pattern analysis, pollution source analysis and ecological risk evaluation are carried out based on the central database, and a pollution traceability report is generated; the method comprises the following steps: constructing a multi-dimensional risk evaluation system, dividing a region into four classes and implementing differentiation management, constructing a governance technology database, screening an optimal scheme based on multiple criteria, performing demonstration verification in a typical region, comparing monitoring data, judging a governance effect and generating a demonstration application summary report; the problems that the soil monitoring and treatment accuracy of the heavy metal mining area is insufficient and the scheme adaptability is poor are effectively solved, and the monitoring and management efficiency and scientificity are remarkably improved.

The invention belongs to the technical field of battery piece management, and discloses a photovoltaic battery piece production batch tracing method, device and equipment and a storage medium. The method comprises the following steps: collecting information related to batches at a key station for photovoltaic cell production; the collected batch information is transmitted to a central database through message middleware for storage management, data in the central database are stored in a layered and subject-divided mode through an ETL tool, and meanwhile information related to batches is sent to a batch association and tracking module; according to the information related to the batch, establishing an association relationship between the raw material batch identification code and each process as well as between the raw material batch identification code and a finished product; and displaying a Web user interface to the user, and performing reverse tracing and forward tracing based on query information input by the user through the Web user interface. Through the batch tracing mode, the traceable data volume index level can be reduced, the cost is reduced, and the raw material tracing requirement of a client can be better met.

The invention relates to the technical field of operation and maintenance of cloud computing equipment, in particular to an operation and maintenance system and method of cloud computing equipment, and the system comprises an operation and maintenance management module, an equipment state monitoring module, a log analysis module, a fault early warning module, an operation and maintenance task scheduling module, a data visualization module and an authority control module. The equipment state monitoring module is used for acquiring running state information of the cloud computing equipment in real time, including CPU utilization rate, memory occupancy rate, hard disk read-write speed, network transmission rate, temperature sensor data and the like, and regularly uploading the running state information to the central database in a multi-thread asynchronous acquisition mode.

The embodiment of the invention provides a ship equipment management system and method based on RFID, and belongs to the field of ship equipment management. The system comprises an RFID electronic tag for storing equipment information, an RFID reader-writer for reading and writing information, a computer terminal, a database, a read-write end management system and a client management system. According to the invention, each piece of equipment is bound with an RFID tag, information of equipment circulation in links of production, warehousing, ex-warehouse, maintenance, replacement and discarding is automatically acquired by using a reader-writer and is synchronized to a central database in real time, and a client management system realizes refined, visual and intelligent management of the equipment in a full life cycle based on the database. According to the invention, the problems of low efficiency, error proneness and difficulty in tracing of a traditional manual management mode are solved, and the management level and decision support capability of ship maintenance support work are remarkably improved.

The invention discloses a data sharing and deployment system and method of a cross-hierarchical regional independent system, and a medium, and aims to solve the problem that global strong-consistency basic data is difficult to manage due to high autonomy of a regional system in the prior art. According to the method, three technologies of service double-instance disaster recovery, CDC real-time data synchronization and Nacos dynamic routing are fused, a mixed mode of central centralized reading and writing and local disaster recovery backup is constructed, two service instances connected with a central database and a local backup database are deployed in each region, data are synchronized to the local backup database in real time by utilizing the CDC technology, and the data are stored in the local backup database in real time. And the online state of the service instance is dynamically adjusted through Nacos, so that the central data is accessed when the network is normal to ensure strong consistency, and the local backup service is automatically switched to ensure high availability when the network fails.

A central database system accesses historical employee spreadsheets along with their modified versions, which have undergone data modification operations. The system creates a training dataset from those spreadsheets to train a machine-learned model. The model is configured to analyze a target employee spreadsheet, identify a historical spreadsheet similar to it, and generate executable scripts based on data modifications performed on the identified historical spreadsheet. The set of scripts is applied to the target spreadsheet to produce a target modified spreadsheet, mimicking historical modification. The modified spreadsheet is sent to an employee spreadsheet processing system for further processing.

The described voting system comprises two main components: an online verification device and an offline voting device. The verification device utilises a data interface to communicate with central databases for real-time voter verification, employing biometric sensors to ensure accurate voter identification and prevent duplicate voting. This system enhances security by generating a unique verification code for each verified voter. The offline voting device, designed to be immune to network-based threats, uses this code along with biometric verification to authenticate voters. It features a user interface that employs eye gesture technology, allowing voters to select candidates privately and securely through eye movements, without any visible indication of their choices to onlookers. This setup not only protects the integrity of the vote from cyber threats but also safeguards voter privacy and reduces the potential for voter intimidation, for a free, fair, and secure voting process.

The embodiment of the invention provides an account management system and method based on a cloud platform, electronic equipment, a storage medium and a program product. The system comprises an account access component, an account management component and an application component, the account access component is used for writing account data of an account to be accessed into the central database; the to-be-accessed account comprises a cloud account of the current cloud platform and a third-party account of a third-party cloud platform independent of the current cloud platform; the account management component is used for managing a cloud account and a third-party account; the application component is used for executing functions corresponding to the application component on the cloud account and the third-party account. Through the account management system provided by the invention, access, management and switching of multiple accounts of multiple cloud platforms can be realized, and the management efficiency is improved.

The invention discloses a data management platform based on a block chain. The data management platform comprises a traceability data storage module and a data consistency management module. Through the traceability data storage module, the traceability data fingerprint of the traceability data is generated, only the traceability data fingerprint is stored in the blockchain account book, a non-tampering evidence is formed, and the storage overhead of the blockchain is reduced. And real traceability data is stored in a central database for subsequent query and review. Through the data consistency management module, the traceability data fingerprints in the blockchain account book and the traceability data in the central database are subjected to consistency management, the data consistency between the on-chain data and the off-chain central database is ensured, and the traceability data is ensured to be credible.

The invention relates to the technical field of file management, in particular to a file cabinet internet-of-things access control and data tracing method. The method comprises the following steps: firstly, generating a multi-site coupling digital key by extracting identity, authority and terminal characteristics of a borrower; during access verification, a dynamic instruction is used as a logic mask to extract effective site features, and a cabinet door is opened when the effective site features are consistent; then, synthesizing a preorder fingerprint with the identity residue of the borrower, writing the preorder fingerprint back to the physical tag, and generating a progressive fingerprint chain by adopting a cascade hash algorithm in a circulation process; and finally, disassembling the fingerprint chain through a reverse analysis model, and restoring the identity of the borrower in each link in combination with a cosine similarity matching algorithm. According to the method, the problems that offline circulation of the archives is non-traceable, authority verification is easy to crack and data highly depends on a central database are solved, and decentralized auditing and responsibility traceability of the archives in the whole life cycle are achieved.

The application discloses a method for real-time deduplication and clustering of long texts, comprising the following steps: step one, infrastructure construction: a data structure capable of quickly fuzzy comparison of feature vectors is established in a central service storage; a text list A with feature values as primary keys is established in a central database; a text list B with feature values as primary keys is established in the central database; step two, coarse classification, real-time calculation when each text in the text list A and the text list B enters the system; step three, timed background modeling; step four, fine classification, timed and quantitative calculation is performed on the text list A, and all similar text pairs thus judged are marked with the minimum feature value in the set as the associated feature value in the table A; and step five, real-time query of terminal users: single text query and time period query, and the application relates to the technical field of data analysis. According to the application, the real-time data processing is ensured, and high accuracy is also considered.

The application relates to the technical field of space governance, and discloses a multi-agent space collaborative governance method, which comprises the following steps: processing multi-source heterogeneous data such as satellite images and sensor readings, establishing cross-type semantic association through geographic space data embedding technology, generating unified structured text after optimizing the satellite image through a vLLM, and synchronizing to a central database; an agent role image is dynamically generated by a central server large language model based on a preset Prompt template, and the generation is independent of fixed rules; then, a target node is selected in an edge-center architecture, a total task is decomposed into subtasks, semantic mapping is established and a matching probability is calculated, and distribution is optimized by means of a reward function; a governance scheme is generated in a perception layer-decision layer-execution layer architecture, and an encoded operation instruction is output; a strategy is updated based on execution feedback, a multistage mechanism is established, roles are automatically redistributed, and governance continuity is ensured. The application can improve the overall efficiency and reliability of space governance when facing dynamic scenes or emergency situations.

We provide the system. [Solution] As a data collection method, a device that collects real-time data from sensors installed at the construction site, A storage means for storing data from the above-mentioned device in a central database, An artificial intelligence processing method that automatically generates construction plans for construction projects using stored data, An adjustment mechanism that detects changes in the external environment and adjusts the construction plan accordingly, A notification means for informing the user of the adjusted construction plan, A learning method that uses the construction results to retrain the system and utilize them in generating the next plan, A system that includes this.

The invention discloses a tobacco process whole flow monitoring method, device and equipment, a medium and a product. The method comprises the steps that in a data processing platform, a central database is connected, to-be-analyzed data are obtained, and the to-be-analyzed data are acquired in real time through Internet of Things equipment of a plurality of to-be-monitored nodes deployed in the whole process of the tobacco technology; performing abnormal data monitoring on the to-be-analyzed data through a control chart theory or a machine learning algorithm, determining an abnormal data monitoring result, and visually displaying a related monitoring chart of the to-be-analyzed data; under the condition that the abnormal data monitoring result indicates that the abnormal data does not exist, optimizing the set process parameters corresponding to the to-be-analyzed data through a deep learning algorithm in combination with a feedback controller, and continuing the process flow through the optimized set process parameters; and when the abnormal data monitoring result indicates that the abnormal data exists, performing abnormal data early warning. According to the scheme, high efficiency and stable quality of related production processes of the tobacco process can be ensured.

The invention relates to a method comprising the following steps: determining (S1) a license number of a preceding vehicle (1) by a following vehicle (3), comparing (S2) the license number with a central database (7) in order to confirm if such a pre-registration is carried out, and if such a pre-registration is confirmed, sending (S3) a request, the absolute position of the preceding vehicle (1) and the absolute position of the following vehicle (3) are in a specified common area, if it is determined that the situation does so, transmitting (S5) sensor information about the other road user (5) by the preceding vehicle (1) to the following vehicle (3), analyzing (S6) the transmitted sensor information, and if it is determined that the absolute position of the preceding vehicle (1) and the absolute position of the following vehicle (3) are in the specified common area, detecting (S4) the absolute position of the following vehicle (3). In order to determine whether the brake light of the other road user (5) is activated, if the brake light has been detected to be activated and the rear vehicle (3) confirms that the brake light of the front vehicle (1) is not activated during this period, the driver of the rear vehicle (3) is displayed with augmented reality a symbol of the activated brake light which is stationary relative to the front vehicle (1).

The invention relates to the technical field of silver powder preparation optimization, in particular to a chemical synthesis silver powder preparation process optimization and production decision-making system based on the Internet of Things, which comprises an Internet of Things data acquisition module, a data transmission and storage module, a silver powder quality prediction model module, a process parameter optimization analysis module, a production decision-making and control module and a human-computer interaction interface. The Internet of Things data acquisition module acquires process equipment environment parameters of multiple key stations; the data transmission and storage module receives the verification data and stores the verification data to the central database; the silver powder quality prediction model module is trained based on historical data and dynamically predicts key quality indexes of the current batch of silver powder; the process parameter optimization analysis module reversely solves and optimizes the process parameter combination; the production decision and control module generates an issuing instruction in combination with the equipment state and the production plan; and the human-computer interaction interface visually displays related information. According to the method, the data reliability, the quality pre-judgment capability and the process optimization accuracy are improved, and intelligent upgrading of silver powder preparation is facilitated.

The invention relates to the technical field of disease prevention and control information, and particularly discloses an animal epidemic disease prevention and control system based on intelligent AI, which comprises a data acquisition module, a data transmission module, a central database module, an individual anomaly detection module, a group propagation prediction module, an intervention strategy optimization module and a decision execution and interaction module. The system collects animal behavior data through the intelligent necklace, adopts double-algorithm fusion analysis to realize accurate identification of individual abnormity, overcomes the problem that epidemic diseases are difficult to find, prevent and control in time in a field grazing environment, constructs a dynamic contact network to predict an epidemic situation propagation path, and applies multi-target reinforcement learning to generate an optimal prevention and control strategy. The intelligent management from individual monitoring to group prevention and control is realized, the accuracy of epidemic disease identification and the timeliness of early warning are remarkably improved, and meanwhile, the prevention and control cost and the influence on the ecological environment are reduced through resource optimization configuration.

The application discloses a cross-factory process parameter intercommunication and interdisplay method based on a unified database and belongs to the technical field of industrial intelligent manufacturing. The application stores all process parameters of production lines into a central database by using existing data acquisition systems of multiple production lines, reads off-line production line data from the database through software logic, and writes back to local HMI display, so that the process parameter intercommunication and interdisplay of long-distance, cross-factory and cross-PLC brand are realized. The application does not need any hardware modification, is not limited by distance and parameter type, and is implemented at zero cost, so that instrument faults and public medium fluctuations can be quickly judged, and the application is especially suitable for long-distance distributed production scenes of multiple production lines in metallurgy, chemical industry and the like.

A multi-functional shopping cart (100) for shopping includes a main storage (102) adapted for storage of items; a top cover (110) disposed on top of, and fixedly coupled to the main storage; a gate (112) provided at the main storage; a crane (130) provided within the main storage and configured to pick up items from the gate and move them to a designated location; an optical device (122) configured to detect the items. The shopping cart further includes a computing device (202) configured to: detect the items; extract one or more attributes of the items; operate the gate to allow the items to enter the main storage; operate the crane to transport the items to their designated location; and transmit the one or more attributes and a log of operations to a central database (250).

A 3D planning table for collaborative layout planning, characterized by a flexible, rollable display (e.g., OLED display or higher) on which additively printed 2.5D miniatures of planning objects (e.g., machines, workstations, etc.) are placed. The current layout state is continuously captured using a 2D or 3D camera and transmitted via an interface to a CAD program, which translates the 2.5D representation into a 3D representation of the layout and displays it on a monitor and via VR glasses. Saved intermediate states can be transferred back to the OLED display via an interface between the CAD software and the planning process. All 2.5D miniatures are equipped with a camera-readable code, which allows further information to be retrieved from a central database using a smartphone camera.