256 results about "Cloud database" patented technology

The invention discloses an intensive rehabilitation treatment decision method based on virtual reality, and relates to the field of medical monitoring, and the method comprises the steps: collecting user physiological state parameters in real time, creating a cloud database, and storing the user physiological state parameters collected in real time based on the cloud database; according to the method, the user physiological state parameters stored in the cloud database are traversed, the wooden barrel model is created based on the user physiological state parameters, and the standard wooden barrel model is synchronously created. The dynamic wooden barrel model is created by collecting the physiological parameters in real time, and accurate comparison with the standard model is achieved in a normalization processing and three-dimensional space alignment mode; the communication area and the risk area can be visually recognized, the abstract limitation of traditional data monitoring is broken through, and dynamic and accurate allocation of medical care resources is achieved in combination with a mobile equipment distance scheduling mechanism.

The invention discloses a hydropower engineering electromechanical equipment installation detail control method based on a three-dimensional laser scanning technology, and the method comprises the steps: S1, setting and determining the instrument parameters of a three-dimensional laser scanner, and collecting the point cloud data of a target region through the three-dimensional laser scanner; s2, remotely reading the point cloud data through a computer, uploading the point cloud data to a cloud database in a file stream form, and storing the point cloud data; s3, performing iterative fitting on the plane model by using a random sample consensus algorithm RANSAC and removing inner points, fitting a target ball model by multiplexing the RANSAC algorithm in the residual point cloud data after the plane model is removed, and screening target ball parameters with the maximum number of inner points; s4, constructing a combined reference model based on the electromechanical equipment to be installed and the virtual target ball, and performing coordinate deviation value comparison with the actually measured target ball model to obtain a deviation value; and S5, generating an installation detail adjustment scheme according to the coordinate deviation value, and sending the adjustment scheme to a mobile client of the field installation personnel.

The invention discloses a chronic obstructive pulmonary disease high risk dynamic assessment model system based on an artificial intelligence algorithm, relates to the technical field of chronic obstructive pulmonary disease high risk assessment, and aims to solve the technical problem that the timeliness and accuracy of an assessment result of an existing assessment model are limited. The medical data acquisition module is used for acquiring medical data of a subject through a wearable device, an electronic medical record system or a manually input multi-source channel, generating standardized preprocessed medical data after performing format cleaning, missing value filling and abnormal value filtering on the data, and transmitting the standardized preprocessed medical data to the memory of the cloud database; and the artificial intelligence dynamic assessment model construction module is used for constructing an artificial intelligence assessment model fusing time sequence characteristics and a nonlinear relationship based on the preprocessed medical data, and generating an intermediate result and a final parameter of risk assessment through multi-level calculation. The method has the advantage that the high risk of chronic obstructive pulmonary disease can be dynamically evaluated in real time.

An elevator health state online monitoring method includes: acquiring parameters such as a position, a three-axis acceleration, an inclination angle, and a noise of a car in a running state of an elevator, left and right brake temperatures of a traction machine, and an environment temperature. Parameter measuring devices are installed on a top of the car and at the brake side of the traction machine. The parameters are collected to a cloud database through a wireless network after being acquired, and a judgment result is given through background automatic analysis. The method is mainly used for monitoring whether key mechanical parts of the elevator are abnormal or not, including guide rail deformation, guide shoe abrasion, car sliding, brake abrasion, adhesion, and the like. This way the health state of the elevator can be automatically monitored, and early warning can be carried out in time when abnormity is found.

Systems and methods for integrating generative artificial intelligence (AI) with real-time data streaming platforms in distributed computing environments are disclosed. A real-time streaming platform receives a natural language input from a client device, stores a corresponding text request in a topic, and generates a prompt using a processing engine. The prompt is provided to a generative AI system, which generates a structured query language (SQL) query. The SQL query is stored in the topic and executed on a cloud SQL database to obtain an SQL result. The SQL result is stored in the topic and a response based on the SQL result is transmitted to the client device. This approach leverages real-time data streaming, automated prompt generation, and AI-driven query construction to facilitate accurate and timely access to distributed data sources.

The invention relates to the technical field of intelligent monitoring of production equipment, in particular to a convenient food production equipment monitoring management method and system. The method comprises the following steps: collecting multi-source data in real time through a multi-dimensional sensor; preprocessing the collected original data; the running state of the equipment is monitored in real time; the abnormal state of the equipment operation state is identified, grading is carried out according to the abnormal severity, and early warning is carried out; generating a maintenance plan, and automatically matching a maintenance work order according to the early warning level; storing equipment operation data, maintenance records and fault cases in a cloud database; the system comprises a data acquisition module, a data processing module, an equipment monitoring module, an abnormity early warning module, a maintenance module and a storage module. Through the above mode, the abnormal state can be recognized in time, and the graded early warning is performed according to the abnormal severity, so that the maintenance personnel can preferentially process the fault which has great influence on the equipment, and the fault processing efficiency and pertinence are improved.

The invention discloses a physical random anti-counterfeiting generation and identification method, which relates to the technical field of anti-counterfeiting, and realizes high-safety, low-cost and easily-integrated anti-counterfeiting and traceability management by generating a unique physical texture through double-overprint micro-dislocation and combining multi-light-source acquisition, phase feature extraction, self-supervised alignment and dynamic threshold judgment. The system can be seamlessly connected with production management systems such as MES, WMS and the like, and supports full-link digital tracing. A unique physical texture is automatically generated on the basis of digital printing double-overprint micro-dislocation, an exclusive fingerprint is injected into each hang tag, binding with a cloud database is carried out through a two-dimensional code, production end generation, circulation end tracking and consumption end one-key verification are achieved, and safety, economical efficiency and large-scale landing are considered; on the premise that the printing cost is not obviously increased, a unique physical fingerprint which cannot be transferred, is difficult to copy and can be quickly read by a machine is generated for each clothing tag, and credible data mapping which runs through factory delivery, circulation and terminal verification is constructed.

The invention relates to the technical field of Internet of Things, and discloses a multi-user equipment access and control method based on a smart cloud platform. The method comprises the following steps: the Internet of Things equipment sends an access request to a smart cloud platform through a network, distributes an access token after verification, and stores equipment information to a cloud database; after the user logs in for the first time, the platform loads a device list according to user account information and a device binding relation, and creates an independent account space; a user sends a control instruction through the terminal, and the platform verifies user permission and converts the instruction into a protocol format which can be recognized by target equipment; the target device executes an operation and feeds back a result, and the platform updates and pushes the result to the user terminal in real time; and the platform continuously monitors the state of the equipment, analyzes and evaluates the state, triggers an early warning mechanism when an abnormity occurs, notifies a user and provides a solution, and the overall efficiency and safety of the system are improved, and the compatibility of multi-user control and the user experience are improved.

The invention relates to internet data services such as databases and cloud database services, more particularly belongs to the field of internet and cloud computing and big data services, and particularly relates to a method and a system for realizing intelligent sorting of data assets based on a self-research algorithm, which comprises the following steps of: constructing an intelligent sorting link of a target database; generating an initial field description set of the target database through a field description generation module of the intelligent carding link; according to the semantic consistency consensus level and the field description accuracy of the initial field description set, establishing a quality evaluation matrix corresponding to the intelligent carding link; according to the quality evaluation matrix, reconstructing a dynamic increment Schema processing mechanism corresponding to the intelligent carding link; and performing vectorization storage on the data assets finally confirmed by the dynamic increment Schema processing mechanism to complete data asset sorting of the business system to be sorted. According to the method, the storage result of the data assets can be ensured, and database Schema dynamic change in a complex business scene can be accurately adapted.

The invention discloses a multi-cloud database consistency automatic inspection method, system and device, and the method specifically comprises the steps: configuring a detection process sequence through an integrated Blockly graphical designer based on early warning information; executing the detection process sequence in an encryption environment, and collecting the instance state, the connection number and the parameter configuration data of the multi-cloud database to form database instance data; analyzing database instance data by using an SHAP framework, and calculating feature importance to locate a root cause causing inconsistency of detection items; and establishing an incidence relation network between the database instance and the application service based on a knowledge graph technology, and positioning an abnormal root cause to a specific service module in combination with the positioned root cause. According to the invention, consistent automatic inspection of the multiple cloud databases is realized, connectivity risks are early warned in advance, abnormal root causes are accurately positioned to specific service modules, and stable operation of the multiple cloud databases is guaranteed.

The invention relates to an electromechanical system energy efficiency scheduling method based on edge-cloud collaboration, and relates to the technical field of computer processing, and the method comprises the following steps: S01, collecting motor operation parameters, environment data and energy consumption data in real time through edge devices deployed at all nodes of an electromechanical system to obtain original data at the same time bit, processing the original data by using an edge computing platform to obtain first processed data; s02, deploying a lightweight energy efficiency analysis model on an edge computing platform, calculating a current energy efficiency value of the motor in real time based on the first processed data, and if the energy efficiency is detected to be lower than a preset threshold value, triggering a local optimization strategy and recording optimization effect data; and S03, storing the optimization effect data uploaded by the edge device into a cloud database. According to the method, efficient, accurate and adaptive management of the energy efficiency of the electromechanical system is realized by constructing an intelligent scheduling architecture with edge real-time response and cloud global optimization collaboration.

This invention relates to the field of primary heating network technology, specifically disclosing a centralized heating primary heating network energy supply balance operation regulation monitoring and control system. The system includes a user area estimated heat demand analysis module, a user area comprehensive heat demand analysis module, an energy station heat distribution module, an energy station heat transmission detection module, an energy station transmission quality assessment module, a display terminal, a protection terminal, and a cloud database. This invention ensures the accuracy and precision of the actual heat supply analysis for user areas, thereby improving the heating efficiency and effect of energy stations. It safeguards the revenue of energy stations on one hand and ensures normal use on the user side on the other. This invention alleviates the pressure on energy stations while meeting the heating needs of users, thereby improving the relative balance of energy stations, reducing the deviation between heat supply and heat demand to a certain extent, and improving the efficiency of centralized energy supply.

The invention discloses a method for realizing lossless switching of agent tasks between basic large models, and relates to the technical field of artificial intelligence. Then analyzing and extracting information from the agent tasks of which the hierarchical categories are determined through an associated metadata template, and carrying out standardization processing to obtain a plurality of standardized agent tasks; processing the standardized agent tasks by a pre-constructed basic large model, recording a processing condition, evaluating and optimizing a basic large model sequence; when an agent task to be processed is processed, the state is processed and monitored according to the optimized basic large model sequence associated with the hierarchical category of the agent task, and the lossless processing flow of the agent task is realized in a mode of lossless switching of the model in the sequence when the state is abnormal.

The invention relates to the technical field of printing equipment, and discloses a control method of thermal printing or thermal transfer printing equipment, a storage medium and a system, and the method comprises the steps that the printing equipment obtains model parameters of a printing medium; the printing equipment obtains environment parameters around the printing equipment; the printing equipment sends the model parameters to the cloud service platform; if the hit item of the model parameter exists in the cloud database of the cloud service platform, the cloud service platform returns a cloud printing parameter corresponding to the model parameter to the printing equipment; if the printing equipment receives the cloud printing parameters, the printing equipment inputs the cloud printing parameters and the environment parameters into an individual correction model to obtain corrected printing parameters, and the individual correction model is obtained by training correction behaviors, collected by the printing equipment, of the user on the cloud printing parameters under different environment parameters; and the printing equipment sets the corrected printing parameters as actual printing parameters of the printing equipment. According to the method, the printing parameters conforming to user preferences can be automatically configured, and the printing experience is improved.

This utility model belongs to the field of shared power bank technology, specifically relating to a voice-interactive shared power bank. The shared power bank's outer shell incorporates interactive and fixing components, integrating intelligent interaction and convenient charging. The interactive components include a waterdrop screen, a voice interaction module, and a network module, enabling voice-guided rental and cabinet location via a cloud database. The waterdrop screen, combined with a recessed button, supports reading during power outages. A wireless charging coil and magnetic plate provide magnetic fast charging for easy operation. The fixing component adopts an L-shaped structure, using a combination of T-slots, silicone strips, and rotating blocks to securely hold the phone when the user moves. The outer shell has a speaker hole and charging port on the side, an input interface on the bottom, and anti-collision pads on opposite sides to cushion impacts, enhance stability, and ensure the device's safety and durability.

The invention discloses an intelligent breast pumping system and a control method. The intelligent breast pumping system comprises a breast pump. The interaction device is in wireless connection with the breast pump, the interaction device is used for sending a control signal to the breast pump to control the breast pump, and the interaction device can update working parameters of the breast pump in real time; the server is internally provided with a cloud database, the server is wirelessly connected with the interaction device, the server is used for sending data to the interaction device, the interaction device is internally provided with an AI module, and the AI module is used for processing information of the interaction module and data in the cloud database. According to the application, the AI module is arranged in the interaction device, and the interaction device is interconnected with the server and the breast pump, so that the interaction device automatically adjusts the currently used function, mode, gear and force of the breast pump in real time and online according to the interaction information of the user, and automatically switches the breast pumping mode, thereby improving the user experience. Therefore, the breast pumping requirements in different time periods and different states are met, and the breast pumping process is more comfortable.

The invention discloses a storage battery based on a two-dimensional code traceability function. The storage battery comprises a storage battery body, an exclusive two-dimensional code identifier, a cloud database, a special management APP and an intelligent polishing tool, the exclusive two-dimensional code identifier is printed through acid and alkali resistant UV ink, covers the polycarbonate transparent wear-resistant coating and is permanently fixed on the battery cover of the storage battery body, and the color of the two-dimensional code and the battery cover form obvious visual contrast; the exclusive two-dimensional code identifier is associated with a unique identity identifier, and the unique identity identifier and storage battery full life cycle data are bound and stored in a cloud database. According to the method, the data reading efficiency is improved, the full-life-cycle data association rate is improved, manual one-by-one retrieval is not needed, complete data of the battery from production to operation and maintenance can be directly obtained through code scanning, errors of data recording and querying are reduced, meanwhile, physical coating and encryption dual protection is adopted for the two-dimensional code, the tampering rate is decreased to 0, and the anti-fake capacity is remarkably improved.

Near-zero downtime maintenance of containerized applications can be achieved via a modified rolling update strategy for a container orchestration platform. During deployment of a first set of containers based on a first deployment that specifies an image of a first software version and a grace period for preserving existing connections to the first set of containers, a second deployment object is received that specifies an image of a second software version and a minimum execution time for a second set of containers after which new connections to the second set of containers are allowed. After deployment of the second set of containers, new connections to the second set of containers are not enabled until the respective containers have executed for the minimum execution time. Existing connections to each container of the first set of containers are preserved until the earlier of their completion or expiration of the grace period.

The invention relates to a database connection method and device, computer equipment, a medium and a program product. The method comprises the following steps: acquiring connection request information and global singleton object data from a client, and obtaining a mapping relationship between an elastic public network address and a virtual private cloud address; obtaining an original response result which corresponds to an original main node confirmation command of the client and comprises address information of the replica set node; under the condition that it is determined that the connection request needs to be subjected to elastic public network address replacement according to the connection request information and the global singleton object data, a virtual private cloud address in the original response result is replaced with a corresponding elastic public network address according to the global singleton object data, and a target response result is obtained; and sending the target response result to the client, and establishing connection between the client and each node of the replica set according to address information in the target response result. By adopting the method, the database connection flexibility can be improved on the basis of ensuring the security isolation of the cloud database.

The invention belongs to the technical field of intelligent reservation management, and particularly relates to a stadium intelligent reservation management method based on a cloud database, and the method comprises the steps: obtaining reservation information data inputted by a user from various data sources; the method comprises the following steps: acquiring reservation data information, extracting morphological time sequence characteristics and semantic time sequence characteristics from the acquired reservation data information, mining entity information from the extracted morphological time sequence characteristics and semantic time sequence characteristics, and fusing the entity information, thereby accurately acquiring the actual demand of a reservation person; and then, based on the fused entity information, coach information is retrieved from a cloud service platform so as to match a reservation person with a coach, and a matching result is output, so that coach data accurately matched with the reservation person can be retrieved from a cloud database.

The invention relates to the technical field of pressure vessel intergranular corrosion detection, in particular to a nonlinear ultrasonic guided wave detection method for pressure vessel intergranular corrosion. The system comprises a signal generation and emission module, a signal acquisition and preprocessing module, a feature extraction and analysis module, a damage positioning and evaluation module, an optimization and calibration module and a data storage and visualization module. According to the invention, through cooperative work of the multi-band excitation signal and the distributed sensor array, the detection sensitivity and resolution are significantly improved; a nonlinear characteristic matrix and a multi-level decomposition capture material nonlinear effect are utilized to realize accurate positioning and evaluation; an adaptive parameter adjustment mechanism simplifies the operation process and reduces the detection cost; and a cloud database and a graphical interface are convenient for result storage and analysis. The intergranular corrosion can be efficiently and reliably detected, and a scientific basis is provided for the industrial field.

A solution for transforming and managing data in a data lake environment is disclosed. A definition of a transformation stream is received via a graphical user interface. The transform stream specifies an operation to transform source data into target data stored in the first format object store. And generating a virtual process corresponding to the transformation stream and storing the virtual process in a memory cloud database. A virtual process is then executed such that metadata is retrieved from the first format object store and a transform job is triggered on the compute cluster. The transform job reads the source data from the first format object store, applies one or more transforms specified in the definition of the transform stream, and writes the result to the target data in the first format object store.

The application provides a non-intrusive intelligent device log tracking system, which comprises a device end integration module, a cloud server module and a cloud database module.The device end integration module is in communication connection with a device to be tracked during use, is configured to obtain log data of the device to be tracked, and uploads the log data confidentially; the cloud server module is in communication connection with the device end integration module, is configured to generate a log tracking strategy of the device to be tracked and receive the log data; the log tracking strategy is used to instruct the device end integration module to obtain the log data according to corresponding operation and maintenance requirements; and the cloud database module is in communication connection with the cloud server module, is configured to store the log data, the log tracking strategy and device data of the device to be tracked.The application solves the problems of inflexible log collection, strong invasiveness and low operation and maintenance efficiency of the existing device tracking technology through the above system.

The invention discloses a data customization production delivery method and system based on a block chain and cloud, and relates to the technical field of data processing and information security, and the method comprises the steps that a data customization party and a production party register and bind a public chain address in the system; deploying an intelligent contract with an automatic fund transfer function on a public chain based on the transaction demand; the customization party prepares a production environment, including creating a production cloud container and a cloud database, and generating an asymmetric key pair; the producer completes data production in the isolated cloud container, encrypts the whole-process data by using the public key of the customizing party and stores the encrypted data into the private block chain; and the system then starts an independent data verification container, decrypts the data by using a built-in private key, carries out integrity comparison and quality verification, and automatically triggers an intelligent contract to carry out settlement according to a verification result. The problems that the data is easy to reuse, the ownership is unclear and the settlement efficiency is low in data customization production are effectively solved, and safe, credible and efficient data production and delivery are realized.

The invention relates to a resource scheduling method and device, computer equipment and a storage medium. The method belongs to the technical field of resource management. The method comprises the following steps: determining tenant feature representation of a target tenant and database feature representation of a cloud database; and performing fusion processing on the time sequence demand feature representation, the tenant portrait feature representation and the task association feature representation to obtain tenant comprehensive feature representation of the target tenant. And determining a resource demand prediction result of the target tenant according to the tenant comprehensive feature representation and the database feature representation. And performing resource scheduling for the target tenant according to the resource demand prediction result of the target tenant. According to the method, the tenant portrait information and the task association information of the target tenant and the resource feature information and the task feature information of the cloud database are considered, so that the resource demand of the target tenant can be predicted more accurately, and the accuracy and rationality of resource scheduling are improved; the database resource utilization rate is improved; and the SLA guarantee of the target tenant is realized.

The embodiment of the invention provides a vehicle automatic test method and related equipment, and belongs to the technical field of vehicles. The method comprises the following steps: acquiring an expected test demand parameter, and uploading the expected test demand parameter to a cloud database to generate a preset test demand instance; acquiring equipment working state information of each piece of preset test equipment, determining target test equipment according to the equipment working state information and the preset test demand instance, and generating a corresponding test task; when it is determined that the test task meets a preset generation condition, generating a target automatic test program through a preset automatic test generation unit according to the preset test demand instance; and executing a test through the target test equipment according to the target automatic test program to obtain a target test result. According to the embodiment of the invention, the automation degree and the testing efficiency of testing work can be effectively improved.

This invention discloses an intelligent analysis and early warning cloud database system for big data in water conservancy project operation and maintenance, specifically relating to the field of water conservancy project operation and maintenance technology. The system is based on a cloud-native architecture and includes an intelligent data lake warehouse, a time-series graph fusion storage engine, an embedded model computation module, a collaborative early warning and analysis module, and a self-learning optimization module. The intelligent data lake warehouse performs semantic annotation preprocessing on multi-source heterogeneous operation and maintenance data; the time-series graph fusion storage engine deeply integrates domain knowledge graphs with semantically annotated time-series data sequences, logically binding the time-series data sequences to graph nodes through globally unique identifiers to form a time-series-graph hybrid data model; the embedded model computation module deploys dedicated analysis models; the collaborative early warning and analysis module aggregates multimodal evidence chains, schedules model collaborative computation, and performs fusion analysis to generate early warnings; the self-learning optimization module optimizes the model online based on feedback. This invention achieves data fusion storage and intelligent early warning, improving operation and maintenance efficiency and reliability.

The application provides a cloud database-based anti-counterfeiting holographic paper authentication information management method and system, applied to the anti-counterfeiting authentication technical field, by establishing the association of identity identification and physical anti-counterfeiting features, and preprocessing the physical features into first feature data and second feature data with different complexities, hierarchical verification is realized. The identity identification is acquired and it is judged whether it is in a state to be checked; only when it is in the state, real-time physical features are collected and first feature data is extracted, and first-level local comparison is performed on a terminal or an edge node. If the matching degree is between preset thresholds, the data is uploaded to the cloud, and the server uses high-precision second feature data to perform second-level comparison to determine the final result. Finally, the identity identification state is dynamically updated according to the verification result, and access control is performed on subsequent requests. Therefore, the scheme has the beneficial effects of reducing the cloud computing load, guaranteeing the verification experience of legal users, and effectively intercepting illegal requests.

The application provides a cloud database processing method and device, an edge device and a storage medium. When the edge device obtains a data processing request sent by a terminal, an application pod in the edge device generates a corresponding cloud database processing request according to the data processing request, and the edge device obtains device attribute information related to the edge device. When the device attribute information meets a device attribute condition, the cloud database processing request is parsed, the operation type of the cloud database processing request is obtained, when the operation type includes a read operation, the request is processed by using a read-only instance stored locally, the data to be read is obtained, and the data is transmitted to the application pod, so that the application pod feeds back the processing result to the terminal after processing the data. Since the read process of the data does not need to interact with a cloud center server, the network delay of the edge device accessing the cloud database in the cloud center server is saved, and the efficiency of the terminal in obtaining information related to the cloud database data is improved.

The invention provides an implementation method of a digital family tree management system based on Spring Boot and Vue3, which comprises the following steps of: adopting a front and back end separation architecture, displaying family information at a front end by utilizing a Vue3 design interface component, and implementing functions of page jump, data addition, deletion, modification and check, user login and registration and the like at a back end based on Spring Boot; system related data is stored in a cloud MySQL database, and a rear end reads and transmits the system related data to a front end for display through SQL statements; the system comprises a personal information tree and family tree structure, and newly added information is uploaded to a cloud database in real time; constructing a prediction model based on a neural network, predicting a change trend of a front-end numerical element, and storing the change trend to a cloud; the system is deployed to a cloud server, and cross-operating-system and multi-terminal access is achieved. Through data set management, front and rear end cooperation, genealogy dynamic visualization, intelligent prediction and cloud integrated deployment, the genealogy management efficiency, the intelligent level and the user experience are improved.