22 results about "Cloud data management" patented technology

The application discloses a kind of light security communication method and system for agricultural perception node.The method includes that 256-bit static master key is preset in the bottom layer security storage area of perception node and heterogeneous convergence gateway, and the unique hardware serial number is read as node identification;Synchronous acquisition environmental data and visual feature data, splice into long payload plaintext;Derive dynamic session key, use dynamic session key to drive stream cipher to encrypt long payload plaintext, static master key drives block cipher to encrypt short header, and encapsulates into data frame;Data frame is sent through wireless channel, and heterogeneous convergence gateway receives and reversely decrypts short header to extract dynamic anti-fake factor, and replay attack verification is carried out;After verification, dynamic session key is reconstructed to restore data and uploaded to cloud data management server.The application also discloses a system using the above light security communication method for agricultural perception node, realizes the high security node legitimacy authentication and anti-replay attack under limited hardware computing power.

The invention discloses a pet personalized meal whole-process service system and method, and relates to the technical field of intelligent pet services, and the system comprises a cloud data and service module and an intelligent cooking execution module. The cloud data and service module is used for establishing and managing pet structured archives, generating quantitative recipes through a catering algorithm based on archive data, associating an e-commerce system to carry out clean vegetable commodity matching and order process management, and storing full-process data, and the full-process data comprises archive updating, cooking feedback and order recording. According to the pet personalized meal whole-process service system and method provided by the invention, through integration of intelligent hardware, cloud data management and e-commerce service, comprehensive personalization and scientization of pet feeding are realized, the problem of unbalanced nutrition in traditional pet feeding is effectively solved, and the pet can be fed according to the specific health condition and nutritional requirements of the pet. A nutrition formula is dynamically generated and adjusted, and pet health is promoted.

The invention belongs to the technical field of high-voltage cable monitoring, and relates to a high-voltage cable metal sheath grounding state diagnosis method and system fusing multiple parameters. And a complete'digital twinning 'closed loop fed back comprises physical world perception, network transmission, cloud data management, multi-parameter fusion, intelligent diagnosis decision, visual presentation, artificial feedback and model self-optimization. A data island is broken through multi-parameter fusion, a leap from'static threshold alarm 'to'dynamic intelligent prediction' is realized through adaptive learning, and finally a predictive maintenance system capable of continuously accumulating knowledge and improving accuracy is formed.

The invention specifically relates to the technical field of aircraft control and navigation, and discloses an intelligent unmanned aircraft trajectory control and navigation system based on multi-source data fusion, which comprises an airborne data acquisition module, a ground cloud data management module, a flight action recognition module, an energy consumption decomposition calculation module, a trajectory calculation calibration module and a trajectory correction control module, flight associated data, flight meteorological data and flight plan data are fused through an airborne data acquisition module and a ground cloud data management module, a flight associated data set is constructed, the trajectory length is calculated in a backstepping manner in an environment without GNSS signals, a high-precision trajectory measurement result of a region without GNSS signals is continuously output, an associated energy consumption coefficient is corrected, and a high-precision trajectory measurement result of a region without GNSS signals is obtained. It is ensured that the mapping relation between the level flight equivalent energy consumption and the flight distance is accurate and reliable, real-time feedback is provided for autonomous navigation and path control of the unmanned aerial vehicle, and the adaptability of the system in a complex environment is remarkably improved.

The invention relates to the technical field of cloud data management, in particular to an emergency data sharing method based on a cloud platform, which comprises the following steps: acquiring cloud emergency data distribution characteristics, access authority and transmission path state, associating three types of data to evaluate overall state identification node connection, analyzing transmission load and bandwidth to evaluate reliability, and sharing the data. And comparing the instruction with the node state, adjusting transmission correction feedback, monitoring a transmission track and load change analysis stability, and outputting a shared path maintenance state label. According to the invention, association verification is carried out by acquiring cloud emergency treatment data distribution characteristics and access levels, so that cross-node data state perception and complete mapping are realized, the transmission direction and rate are automatically adjusted according to load change and network stability, and balanced transmission and reliable output under multi-node cooperation are ensured; and the transmission track change is continuously monitored to keep the sharing period stable, so that the data flow is kept continuous, safe and efficient in a complex cloud environment, and the emergency data sharing real-time performance and consistency are improved.

The present application relates to a kind of ship construction flatness inspection equipment and its use method, belong to ship flatness inspection technical field, including magnetic adsorption type mobile robot platform, magnetic adsorption type mobile robot platform, high-precision vision module, edge computing unit, cloud data management platform, magnetic adsorption type mobile robot platform is provided with track type walking mechanism and adaptive vacuum adsorption unit.In the present application, efficient, high-precision full-ship flatness intelligent detection can be realized by multi-sensor fusion and adaptive robot platform, suitable for real-time quality monitoring of hull block construction, deck assembly and outfitting stage, can perform local fine scanning along the weld area in the hull block detection scene, simultaneously mark the welding deformation out-of-tolerance area, can be switched to global fast scanning mode for non-key plane area, in deck assembly stage, cloud platform can integrate data in real time, assist in carrying out assembly misalignment correction scheme.

The invention relates to the technical field of cloud data management, and particularly discloses a resource scheduling management system and method based on a cloud platform, and the method comprises the steps: obtaining heterogeneous resources from cloud platform resources, carrying out the information collection of the heterogeneous resources through a heterogeneous data interface, carrying out the same-type division of the heterogeneous resources, and obtaining heterogeneous resource nodes, the method comprises the steps of obtaining historical resource scheduling data of equipment, performing resource scheduling feature extraction and time sequence analysis, constructing a resource scheduling feature vector, performing similarity matching, determining equipment scheduling heterogeneous resource nodes, establishing a dynamic load prediction algorithm, performing fitting analysis on a load trend in combination with a sliding window, predicting load change and generating a scheduling early warning signal. And in combination with a resource priority strategy, a resource allocation scheme is obtained, task migration is performed on high-load heterogeneous resource nodes, and the migration tasks are allocated to the same type of heterogeneous resource nodes with low loads, so that optimization of resource allocation is facilitated, and the resource utilization rate of the cloud platform is improved.

The application discloses a kind of ship-shore cloud intelligent platform, ship intelligent management method and storage medium, ship-shore cloud intelligent platform includes ship end edge processing module, cloud intelligent analysis module, cloud data management module, dynamic transmission control module;Ship end edge processing module is used to collect the data of ship sensor, and the data is sent after edge side pretreatment;Cloud intelligent analysis module is used to receive the data after pretreatment, and the field model is established based on the multidimensional correlation of data, and the state result of each functional module is calculated and generated;Cloud data management module is used to store and manage the correlation of data based on the field model;Dynamic transmission control module is used to dynamically adjust the data sampling strategy of the ship end edge processing module according to real-time data flow.The application solves the problem of abnormal function, insufficient real-time function caused by high satellite signal interruption and propagation delay in the existing ship intelligent platform.

The invention discloses an elevator Internet of Things abnormity diagnosis data management method and system. The method comprises the following steps: collecting heterogeneous time sequence data of an elevator and carrying out time alignment; performing real-time anomaly detection, data cleaning and adaptive compression on the edge computing node; uploading the processed data to a cloud, extracting and intelligently fusing multi-source features, and forming a unified feature vector; outputting an anomaly type, a severity level and a fault root cause chain by using the dynamic anomaly diagnosis model; and based on historical data and feature vectors, predicting the remaining service life of the key component through a fusion model, and generating a maintenance strategy by using a reinforcement learning optimization engine. The system comprises a physical sensing layer, a data acquisition and edge processing layer, a cloud data management and intelligent analysis layer and an application service layer. According to the elevator abnormal diagnosis system and method, full-process intelligent management from real-time monitoring and accurate diagnosis to predictive maintenance is achieved, and the accuracy, timeliness and operation and maintenance efficiency of elevator abnormal diagnosis are remarkably improved.

The embodiment of the invention provides a data processing method and device, electronic equipment and a storage medium, and relates to the technical field of Internet. The data processing method comprises the steps of obtaining a resource processing application sent by a data demand terminal; updating a first use record of target resource data in the cloud data platform based on the resource processing operation; if an update completion message for the first use record of the target resource data sent by the cloud data platform is received, sending an update notification to a private cloud data management platform, so that the private cloud data management platform updates a second use record of the target resource data in the private cloud data platform; if the preset verification condition is met, reading a first use record of each piece of resource data in the cloud data platform, and reading a second use record of resource data in the private cloud data platform; and matching the first use record and the second use record of the same resource data to obtain a data verification result. The accuracy of resource data use can be ensured, and resource abuse is prevented.

The invention relates to an electrocardiogram monitoring system and method based on a twelve-lead system, and relates to the technical field of remote medical information processing, and the electrocardiogram monitoring system comprises an electrocardiogram signal acquisition terminal, a wireless communication transmission network, a cloud data management analysis platform and a remote monitoring interaction terminal, an analog front end and master control communication separated framework is adopted in the electrocardiosignal collecting terminal, a Wilson central electric end is synthesized through a resistance network to collect high-fidelity signals, a transmission network supports multi-mode self-adaptive switching, a partition storage and breakpoint resume strategy containing an abnormal event write-protection mechanism is started when the network is disconnected, data integrity is guaranteed, and the reliability of the electrocardiosignal collecting terminal is improved. The cloud platform generates diagnosis data by using a Demix superposition technology and an ST-T feature analysis algorithm, the remote terminal provides waveform rendering, electronic caliper gauge measurement and manual correction feedback functions, and the system solves the problems of easy signal interference, weak network data loss and low automatic diagnosis accuracy in remote monitoring.

The invention discloses an intelligent education cloud data management method and system based on modular design, and the method comprises the following steps: S1, building a standardized metadata model based on the multi-source heterogeneity of education data, and dynamically adapting to an acquisition module; s2, deploying independent functional unit modules on the cloud platform, constructing a reconfigurable assembly line through a standardized interface between the modules, automatically matching a processing path according to a data type, and outputting an incremental data set with a uniform format; s3, based on the access permission tree associated with the role, creating a logic storage partition bound with the teaching role; s4, the analysis demand is disassembled into micro-service computing nodes, and a multi-dimensional education analysis result is generated; s5, deploying an independent security monitoring module, and generating a periodic compliance audit report; according to the method, a module cascade feedback and security audit double-circulation mechanism is constructed, the problem of system module splitting is solved, a whole is formed under an interface framework, and the privacy protection strength, the scheduling efficiency and the behavior tracing reliability are improved.

The invention relates to the technical field of power system monitoring, and discloses a hydropower station unmanned vehicle inspection system, method, device, equipment, medium and product, the system comprises a cloud data management center, a plurality of edge computing units and a plurality of unmanned inspection vehicles; the cloud data management center is used for generating inspection task information of a plurality of areas in the hydropower station according to an equipment list and an inspection period of the hydropower station, and issuing the inspection task information of each area to the corresponding edge computing unit; each edge calculation unit is connected with at least one unmanned inspection vehicle in the corresponding area, and is used for updating the space-time task graph of the corresponding area according to the inspection task information to obtain a target space-time task graph; performing task allocation and inspection path planning on the unmanned inspection vehicles in the corresponding area based on the state data of the unmanned inspection vehicles in the corresponding area and the target space-time task graph to obtain an inspection instruction; the unmanned inspection vehicle is used for executing an inspection task according to the inspection instruction.

The invention relates to the technical field of automatic driving, and discloses an automatic driving simulation test system and equipment. A terminal user configuration interface issues a simulation task with a target scene to a central scheduling program and visualizes a process; the central scheduling program receives the simulation tasks and issues the simulation tasks to the distributed simulation calculation nodes through the message middleware, a global task scheduling engine is constructed, and a test whole process is constructed and executed as an automatic workflow; the message middleware adopts an asynchronous communication mechanism to provide a message transmission channel; the terminal scene database writes simulation task full-process data, and scene resources are encrypted and obtained from the cloud data management platform; after the distributed simulation calculation nodes confirm that the simulation task is received through the vehicle networking interaction module, corresponding data of a target scene are pulled from a terminal scene database, and a simulation engine is called to load and execute the target scene. The technical problems that an existing system is insufficient in flexibility and expandability, scene management is disordered, the process automation degree is low, and safety is weak are solved.

This invention relates to the field of autonomous driving technology and discloses an autonomous driving simulation testing system and equipment. The system allows end-users to configure an interface that sends simulation tasks with target scenarios to a central scheduler and visualizes the process. The central scheduler receives the simulation tasks and, via a message middleware, sends them to distributed simulation computing nodes, building a global task scheduling engine to automate the entire testing process. The message middleware uses an asynchronous communication mechanism to provide message transmission channels. The terminal scene database writes the entire simulation task process data and encrypts scene resources from a cloud data management platform. After confirming receipt of the simulation task via a vehicle-to-everything (V2X) interaction module, the distributed simulation computing nodes retrieve the corresponding target scenario data from the terminal scene database, call the simulation engine to load the target scenario, and execute it. This invention solves the technical problems of insufficient flexibility and scalability, chaotic scene management, low automation, and weak security in existing systems.

The invention provides a wearable knee joint rehabilitation training angle monitoring system after knee joint replacement, and the system comprises a wearable monitoring unit, a CPM machine adaption unit, a cloud data management unit, and a multi-terminal display unit, and is provided with a wearable inertial sensing module, a CPM machine adaption module, a cloud data processing module, and a multi-terminal display module. And integration of cooperative monitoring and autonomous monitoring of the CPM is realized. The system can be in butt joint with an existing CPM, the knee joint angle is calculated through the nine-axis IMU in combination with the self-adaptive Kalman filtering algorithm, and when the deviation exceeds a threshold value, the stroke of the CPM is automatically and finely adjusted; angle monitoring and action early warning can be independently realized in the mode, and the training data synchronization cloud supports remote evaluation. The knee joint rehabilitation training device is compatible with existing equipment, light and wearable, solves the problem of out-of-hospital fault of knee joint rehabilitation training, improves rehabilitation safety and individuation degree, and is suitable for orthopedic postoperative clinical rehabilitation scenes.

This invention discloses a patient education system and method based on augmented reality (AR) scenario simulation. The system includes an AR wearable terminal, a motion capture and data acquisition device, a virtual scene construction and interaction device, an intelligent assessment and feedback device, a cloud data management device, and a medical staff terminal. Medical staff input patient information and push suitable scenarios through the medical staff terminal. Patients wear the AR wearable terminal to enter the virtual scene. The motion capture and data acquisition device collects movement trajectories and electromyographic signal data, which are calibrated and fused for scene branch evolution and movement deviation analysis, generating an assessment report and pushing personalized supplementary educational content. This invention achieves immersive and precise patient education, improves patient participation and educational effectiveness, and reduces the burden on medical staff.

This invention discloses an intelligent maintenance robot integrating inspection and tightening of wind turbine tower bolts and its operation and maintenance method, belonging to the field of wind power operation and maintenance robot technology. It solves the industry pain points of existing tower bolt manual high-altitude operations, such as high risk, separation of inspection and maintenance, poor torque accuracy, lack of data traceability, and traditional robots only tightening without inspection or only inspecting without tightening. This robot includes a magnetic suction autonomous walking unit, an AI three-dimensional vision defect detection unit, a high-precision torque sensing inspection and tightening execution unit, a lifting and fine-tuning module, and an edge control and cloud data management unit. The magnetic suction wheel autonomously cruises along the circumference of the flange on the inner wall of the tower, visually completing the appearance inspection of bolt corrosion, missing gaskets, and cracks. After the sleeve is coaxially aligned, the residual preload is detected in situ. If it is lower than the design threshold, it automatically closes the loop to tighten. Bolts that meet the standard are skipped for tightening. After tightening, the torque is re-inspected, and all parameters are archived in the cloud. This invention achieves fully automated operation integrating appearance quality inspection, residual torque detection, intelligent re-tightening, re-inspection, and electronic filing, significantly reducing the risks of high-altitude maintenance, improving the consistency of bolt maintenance and the level of digital management throughout the entire life cycle, and is suitable for routine maintenance of M36~M72 high-strength bolts for all specifications of wind turbine towers on land and offshore.

Methods, systems, devices, and computer-readable media used by a cloud data management system for collecting data from accounts hosted by a cloud-based data storage system on different cloud platforms or in different cloud regions of a cloud platform. Collection of data in the multi-cloud platform and / or multi-cloud region environments may be facilitated by the on-demand creation of one or more data collection accounts. Based on the collected data, one or more recommendations, notifications, or alerts associated with usage of the data storage system may be generated.

The invention discloses a gas chromatographic analyzer based on cloud data management and a gas component detection method. The analyzer comprises a sample introduction module, a separation module, a detection module, an analysis module and a communication module. The separation module adopts a chromatographic separation column filled with a hydrophobic modified stationary phase material, and chromatographic separation of hydrogen and methane is realized under the pushing of air carrier gas. The detection module judges the effectiveness of a sample through carbon dioxide concentration detection and distinguishes alveolar gas and oral cavity dead space gas. The separation optimization unit adjusts the carrier gas flow and / or the column temperature to enable the retention time difference to meet a preset condition, pulse heating control accelerates baseline recovery, and overlapping of adjacent peaks is avoided. And the communication module is connected with a cloud server to realize uploading of detection data and remote updating of drift compensation parameters. According to the invention, the dependence on high-purity inert carrier gas is eliminated, the use cost is reduced, and the reliability of a detection result is improved.

The utility model provides a kind of water conservancy pipe network multi-parameter fusion water hammer monitoring device, comprising: water pump, pump station water outlet mother pipe, pipeline, check valve and water delivery pipe;The fixed flange is arranged between the water pump and the pipeline, the middle fixed installation of the fixed flange one side is equipped with assembly pipe, the surface of the assembly pipe inner cavity wall is equidistantly surrounded and fixedly connected with multiple support blocks, and the side fixed installation of the support block is equipped with guide cone pipe.The utility model provides a kind of water conservancy pipe network multi-parameter fusion water hammer monitoring device, by fusing pressure, flow, vibration, rotational speed and so on Parameter, avoid single parameter misjudgment, reach multi-dimensional monitoring accuracy, built-in coupling analysis model, real-time calculation water hammer pressure envelope and pipe network weak point, shorten fault response time, improve risk assessment accuracy, support cloud data management, compatible pipe network whole life cycle model updates, adapt to water hammer protection strategy optimization under different working conditions, system expansibility is high.

Methods, systems, devices, and computer-readable media used by a cloud data management system for collecting data from accounts hosted by a cloud-based data storage system on different cloud platforms or in different cloud regions of a cloud platform. Collection of data in the multi-cloud platform and / or multi-cloud region environments may be facilitated by the on-demand creation of one or more data collection accounts. Based on the collected data, one or more recommendations, notifications, or alerts associated with usage of the data storage system may be generated.