143 results about "Cloud management" patented technology

Disclosed are a server system based on public cloud technology, an instance creation method and a cloud management platform, and belong to the technical field of cloud services. The server system comprises a first server and a second server connected by a connection channel. A first instance of the first server is provided with a first business module and a first security module; a second instance of the second server is provided with a second business module and a second security module; the first business module is used for sending an access request for the second business module, and the access request is used for requesting the second business module to provide a second tenant service; the first security module is used for obtaining the access request, encrypting the access request, and sending the encrypted access request to the connection channel; and the second security module is used for obtaining the encrypted access request from the connection channel, decrypting the encrypted access request, and sending the decrypted access request to the second business module. The application realizes end-to-end encryption protection of the access request.

The application belongs to the field of cloud computing, and is a management method of a computing power cloud architecture combining a container cloud and a virtual machine cloud, a cloud management platform, a host resource management layer and a resource access layer, and comprises the following steps: S1: a host resource management module registers with the cloud management platform; S2: a registration and scheduling module sends a container creation instruction, and a host creates and schedules a container; S3: the host resource management layer reports idle resource information to the cloud management platform, and the cloud management platform triggers the binding and deployment of the container and the host; S4: a virtual machine access module sends a virtual machine creation instruction, and deploys a virtual machine to a specified host; S5: a resource access layer respectively collects and reports the running states of the container and the virtual machine; S6: a container state monitoring module sends a container unbinding and destruction instruction, and a host resource management module executes the operation; S7: a virtual machine host module sends an unbinding instruction, executes virtual machine unbinding, and a resource access layer releases resources.

Disclosed are a server system based on public cloud technology, an instance creation method and a cloud management platform, belonging to the technical field of cloud services. The server system comprises a first server and a second server, between which connection channels are established. A first service module and a first security module are provided in a first instance of the first server; a second service module and a second security module are provided in a second instance of the second server; the first service module is configured to send an access request for the second service module, the access request being used for requesting the second service module to provide a second tenant service; the first security module is configured to acquire the access request, encrypt the access request, and send the encrypted access request to the connection channel; and the second security module is configured to acquire the encrypted access request from the connection channel, decrypt the encrypted access request, and send the decrypted access request to the second service module. The present application implements end-to-end encryption protection of access requests.

This utility model discloses an intelligent storage box for turnout hand cranks, including an intelligent storage box body and a door hinged to one side of the intelligent storage box body. An electrical partition is fixedly connected to the inner wall of the intelligent storage box body, and a processing terminal is installed at the upper end of the electrical partition. Multiple sets of turnout hand cranks are installed on the mounting frame assembly, and each set of turnout hand cranks is equipped with an electronic tag. A communication module is used to establish a connection between the intelligent storage box and an external network, transmitting data such as the time the turnout hand cranks are taken, their storage status, and the time the electronic lock is unlocked to the station management cloud platform in real time. The station management cloud platform, as a cloud management platform, stores various information and operation records of the turnout hand cranks, providing an operation interface for relevant personnel such as the electrical section and the station dispatching department. It supports functions such as online application, authorization approval, status query, and historical record tracing, realizing remote intelligent management of the hand cranks.

The application discloses a work area safety event processing method and system and a medium, relates to the technical field of industrial safety production management, and is applied to a cloud management and control platform, and comprises the following steps: receiving event information of a violation event in a work area; the event information is recognized by analyzing a video stream of the work area by an edge device through a target detection model; based on the event information, determining an event type and a processing level from a preset event type configuration table; according to the event type and the processing level, determining a disposal strategy combination of the violation event from a preset closed-loop mode configuration table; the disposal strategy combination refers to a set of differentiated processing execution rules corresponding to different event types and processing levels; and performing a corresponding disposal action according to the disposal strategy combination. The application can meet the safety management requirements of different projects or stages, reduce the false positive rate, and improve the overall work area safety production management efficiency.

The application discloses a kind of based on thumbnail encryption image's authenticatable user end watermark method, belong to computer security technical field. Including: image pre-processing, image encryption, key generation and distribution, decryption and watermark embedding, tamper detection and positioning, tamper content recovery, extract watermark lock user identity.The present application is based on the holographic redundancy embedding of thumbnail and the fine authentication based on parity check, with very strong anti-shearing and self-healing ability;Using the disturbance of pair of pixel difference value, all image pixels can be embedded watermark, and the security blind area is eliminated;Encrypted image has clear identifiable thumbnail, and is highly similar to plaintext, which is convenient for cloud management, and the details privacy is effectively protected through high-frequency information confusion;Encryption and watermark embedding are fused in bottom algebra operation, and the calculation efficiency is high.

This application discloses a logical node management method and cloud system based on cloud computing technology, belonging to the field of cloud service technology. The method includes: a cloud management platform creating a target logical node in the infrastructure, wherein the target logical node includes a virtual CPU, a first virtual extended processor, and a virtual bus network, the virtual CPU and the first virtual extended processor being logically connected to the virtual bus network respectively; if the cloud management platform confirms that at least one first extended processor in the extended processor device pool has failed, it unloads the first virtual extended processor from the target logical node; the cloud management platform then attaches a second virtual extended processor to the target logical node, the second virtual extended processor implementing all or part of the functions of at least one second extended processor in the extended processor device pool, the second virtual extended processor being logically connected to the virtual bus network. This application improves the utilization rate of cloud resources.

This invention relates to the field of photovoltaic power plant operation and maintenance technology, and discloses a cloud-edge-device collaborative intelligent cleaning operation and maintenance management system and method for photovoltaic power plant clusters. The system includes: an end device execution module, an edge decision arbitration module, and a cloud-based global optimization module. It collects and generates multi-source sensing data through the end device layer, and processes this data through the edge computing layer to generate local decision commands and cleaning status data, ensuring comprehensive and real-time perception of the surface status and environmental information of photovoltaic modules. Simultaneously, it rapidly generates cleaning control strategies at the edge based on this data, enabling real-time response to local environmental changes and sudden staining conditions, ensuring the accuracy and timeliness of cleaning decisions, and reducing decision-making biases caused by information lag and omissions. Through the cloud management layer, it integrates multi-source information to generate global strategies, improving overall power generation revenue while considering local operating condition adaptability, ensuring the rationality and efficiency of cleaning task scheduling in complex scenarios.

This application discloses a device testing method, a collaborative testing system, and a readable storage medium, relating to the field of device testing technology. The method is applied to a collaborative testing system, which includes a terminal device layer, an edge computing layer, and a cloud management layer. The system comprises: the cloud management layer receiving test requirements input by a user, generating a test task list based on the test requirements, and distributing the test task list to the terminal device layer and the edge computing layer; the terminal device layer collecting test data according to the test task list and transmitting the test data to the edge computing layer; the edge computing layer executing test tasks according to the test task list and the received test data, obtaining test results, and uploading the test results to the cloud management layer; and the cloud management layer analyzing the test results and generating a test report. This application improves the real-time performance of device testing.

This application discloses a data management method and a cloud management platform based on a cloud management platform, which can improve user experience. The method includes: a user sending a data processing request to the cloud management platform; the cloud management platform obtaining the arrival time of the data processing request in a first period and notifying the primary storage node to provide the arrival time of the data processing request in a second period; the cloud management platform selecting a third period with the latest end time from the first and second periods; the cloud management platform notifying the primary storage node to process the user's data and synchronizing the processed data to the backup storage node; and the user sending a data access request to the cloud management platform; the cloud management platform determining whether the arrival time of the data access request is earlier than the end time of the third period; if so, the cloud management platform notifying the backup storage node to return the data before processing; otherwise, the cloud management platform notifying the backup storage node to return the processed data to the user.

This invention provides an edge computing-based fault prediction and health management system for wellhead equipment, relating to the field of wellhead equipment monitoring technology. It includes an edge node layer, a cloud management layer, and a cross-site federated collaboration layer. The edge node layer is deployed at the wellhead site for on-site preprocessing, fault prediction, and health assessment of wellhead sensor data. The cloud management layer is deployed at the oilfield monitoring center. This invention utilizes a lightweight edge-end fusion preprocessing architecture with a built-in multi-protocol adaptation stack, enabling plug-and-play adaptation to mainstream oilfield industrial protocols such as Modbus, CANopen, LoRaWAN, and HART. This solves the compatibility issues of sensors from different manufacturers, eliminating the need to modify existing sensors and reducing deployment costs. An improved translation-invariant wavelet denoising algorithm is optimized for low-computing-power edge scenarios, effectively eliminating noise interference caused by wellhead operating condition fluctuations at the edge.

The present application relates to the technical field of battery management, and particularly refers to a battery use life cycle management system. The system comprises a battery identification module, a multi-source data acquisition module, an edge computing processing module, a cloud management platform, an intelligent management and control module, a gradient utilization matching module and a recycling closed loop module. The modules communicate with each other to form a whole-process collaborative management system. The system realizes battery whole life cycle data connection, integrates production, storage, use, maintenance and recycling data through double identity identification and multi-source data acquisition, forms a complete traceability system, solves the data fragmentation problem, realizes battery whole-process traceability and controllability, improves battery health assessment and prediction accuracy, combines edge computing and lightweight AI model to realize real-time and accurate calculation of SOH and RUL, simultaneously fuses double factors of cycle attenuation and calendar attenuation, and controls the prediction error within 5%, which can early warn safety risks, avoid sudden failures, delay battery attenuation and prolong battery service life.

A method of collecting and reporting inventory of resources deployed in a data center that includes hardware resources, a virtualization management software executed to provision virtual resources from the hardware resources, and a cloud management server executed to provision the virtual resources for tenants of the data center, includes the steps of: executing a first API call to the virtualization management software to collect first inventory of virtual resources deployed in the data center and a second API call to the cloud computing management software to collect second inventory of virtual resources deployed in the data center; storing the first and second inventory; and in response to an inventory request from a central orchestrator, initially sending a subset of the stored first and second inventory to the central orchestrator in accordance with parameters included in the inventory request, and thereafter sending updates to the subset to the central orchestrator periodically.

This invention belongs to the field of road engineering technology, specifically relating to an integrated self-adhesive rubber asphalt asphalt crack repair and monitoring system. The system includes: a self-adhesive rubber asphalt composite material layer for filling cracks and absorbing stress; a flexible sensing network unit embedded within the layer to sense strain and temperature; a data acquisition and signal conditioning module; a self-powered energy capture system that utilizes ambient energy to power the system; an edge computing terminal for localized damage assessment; and a remote cloud management platform. This system improves bonding strength and low-temperature flexibility through material modification, and combines embedded sensing and self-powered technology to achieve a leap from passive filling to active sensing of the repair body. It solves the problems of difficult power supply in the field and lack of coordination in monitoring, enabling real-time feedback of the interface mechanical state, significantly improving the scientific nature and predictability of highway maintenance, and reducing overall operation and maintenance costs.

The application discloses a tire monitoring management system, method, equipment and medium, and belongs to the technical field of tire monitoring. The system comprises a perception layer, an intelligent sensor module implanted in a tire body, which is used for collecting multi-dimensional state data of the tire in real time; a transmission layer, a vehicle-mounted gateway, which is used for receiving data sent by the intelligent sensor module and reporting to the cloud; and an application layer, a cloud management platform, which is used for constructing a tire digital twin model based on the multi-dimensional state data and performing tire monitoring, tire warning and tire retreading determination. The application solves the technical problem of whole-process monitoring of the tire life cycle by digital modeling and cloud platform management of tire data.

The present application relates to a kind of humanoid robot OTA automatic upgrading method and system, it relates to the field of robot software maintenance, it includes: based on robot state information to determine target robot set;Batch upgrade task is issued to target robot set, and is installed and upgraded with silent installation method;Current battery capacity of robot is collected;If current battery capacity is lower than upgrade maintenance threshold, determine the nearest target charging area according to current robot position;Based on current robot position to determine idle robot, and control idle robot to carry current robot to target charging area and charge, while completing silent installation process in target charging area;After installation upgrade is completed, automatically run self-checking program to verify core function, when upgrade self-checking result meets the preset self-checking requirement result, mark the version information after upgrade as upgrade success and report to cloud management platform.The present application has the effect of improving the upgrading efficiency of robot.

Provided are a cloud application deployment method, a cloud application deployment apparatus and a computing device cluster. The cloud application deployment method is applied to a cloud management platform. The method comprises: a cloud management platform acquiring a resource request inputted by a user; on the basis of the resource request, determining a target region from among a plurality of regions, wherein cloud resources in the target region meet the resource request; and deploying a target cloud resource in the target region. The resource request may comprise a category, a specification and / or a service indicator of the target cloud resource. In the method, a user is not required to sense each region in a cloud platform, and a cloud management platform automatically performs region selection on the basis of a resource request of the user, such that resources of each region can be maximally utilized, and the resource utilization rate is thus improved. Moreover, the method shields the user from differences between regions in the cloud platform, thereby realizing regionlessness. In other words, the user is not required to select a region when deploying a cloud application, such that the difficulty for the user in deploying the cloud application can be reduced.

This application provides an instance management method based on cloud computing technology. The method is applied to a cloud management platform that manages at least one compute node. At least one instance runs on the first compute node. The method receives a first instance creation request from a tenant, which includes the first instance's deployment information, specifications, and priority information. Based on the first instance creation request, a first instance is created on the first compute node. The priority of the first instance differs from that of the at least one instance, and the first instance runs on resources on the first compute node that meet the first priority. During the operation of the first instance, when the instance's priority is dynamically adjusted, the cloud management platform can directly adjust the corresponding resource policies on the compute node. This improves the ability to dynamically adjust to agile business needs while ensuring high availability and reliability of tenant instances, thereby increasing resource utilization on the compute node.

The application discloses a request sending method and device, equipment and a storage medium, relates to the computer technical field, and is used for solving the security risks of the current cloud management platform data, and comprises the following steps: receiving a user access request and determining a corresponding target virtual machine; detecting the target virtual machine based on a preset detection mode to obtain a corresponding detection evaluation report; and when the detection evaluation report shows that the target virtual machine has no vulnerability, sending the user access request to a target area based on a preset data processing rule. The application detects the target virtual machine, judges whether to forward the user request according to the obtained detection evaluation report, does not forward the user request when the target virtual machine has a vulnerability, and improves the security of the data and reduces the use difficulty of the user.

This application provides an intelligent management system for integrated sports fields. By organically combining user terminals, sensing and execution devices, edge computing servers, and a cloud management platform, it constructs a full-link intelligent management system covering "user interaction - data collection - local real-time processing - cloud-based in-depth analysis." Addressing pain points in traditional sports field management such as cumbersome reservations, delayed status perception, and insufficient data support, this system utilizes edge computing and local AI model deployment to achieve real-time response to local events, avoiding response delays caused by cloud transmission latency. Simultaneously, it leverages the big data analytics capabilities of the cloud platform to provide data support for operational decisions. This combination satisfies both the immediate needs of on-site management and the decision-making requirements of macro-operation, thereby comprehensively improving the management efficiency and service quality of integrated sports fields and realizing intelligent collaboration among "people, equipment, venues, and data" in sports scenarios.

The application discloses a general humanoid robot cloud management and control system and method, relates to the technical fields of intelligent robot control, cloud computing and man-machine interaction, and solves the technical problems of single scene adaptability, unreasonable interaction logic, insufficient offline voice recognition disclosure and fuzzy right claim protection range of the existing humanoid robot management and control platform. The system comprises a cloud management and control platform 1, a user terminal 2 and a terminal humanoid robot 3. The cloud management and control platform is provided with an instruction analysis unit, a task scheduling unit, a multi-scene semantic path planning unit and a state monitoring unit, and realizes unified scheduling of robots in all scenes. The terminal humanoid robot is provided with a general ontology shell, is suitable for rigid and flexible materials, is internally provided with a lightweight offline voice recognition module and a man-machine interaction feedback module, can independently operate offline, and can realize remote management and control after being connected to a network and being synchronized with the cloud. Through the design of a coordinate + label type semantic map, a lightweight high-frequency instruction set and a scene-adaptive man-machine interaction, the application realizes compatibility in all scenes of families, businesses and industries, can stably operate without depending on a large model, the technical solution is logical and rigorous, the disclosure is sufficient, the patent protection range is comprehensive and there is no examination risk.

This application discloses an anomaly localization method and a cloud management platform based on a cloud management platform, which can improve the efficiency of anomaly localization to a certain extent. The method includes: the cloud management platform can create a large-scale computing node cluster for tenants, which can contain multiple computing nodes. If these multiple computing nodes fail to execute a job task, the cloud management platform can first obtain the logs generated by these multiple computing nodes during the execution of the job task, and generate log space characteristics and log time characteristics of these multiple computing nodes based on the logs. Then, the cloud management platform can evaluate these multiple computing nodes based on these log space characteristics and these log time characteristics to obtain evaluation values ​​for these multiple computing nodes. Subsequently, the cloud management platform can identify computing nodes whose evaluation values ​​are greater than or equal to a preset threshold as computing nodes that have experienced an anomaly.

The invention discloses a data sampling method based on a cloud management platform and the cloud management platform. The user experience can be improved. The method comprises the steps that a user can send a data sampling request to a sampling interface provided by a cloud management platform, the cloud management platform can receive the data sampling request sent by the user through the sampling interface, the data sampling request can be used for indicating a first key range set by the user, and the cloud management platform can obtain a key value distribution table, a plurality of key ranges and the number of values corresponding to each key range are recorded in the key value distribution table, and the plurality of key ranges are obtained by dividing a plurality of keys in a plurality of key value pairs of the user by the user. And then, the cloud management platform can detect whether a first key range set by the user contains a second key range in a plurality of key ranges recorded in the key value distribution table, and if so, the cloud management platform can generate a data sampling result based on the number of values corresponding to the second key range, and return the data sampling result to the user.

The application provides a kind of intelligent monitoring early warning of unmanned warehouse and its cloud management method, it is related to warehousing intelligent technology field, including intelligent perception network layer, fusion processing hub data layer, intelligent early warning decision engine layer and cloud management application layer, data acquisition is carried out by setting intelligent perception network layer, then by fusion processing hub data layer to multi-source heterogeneous data is time-space alignment and semantic fusion, constructs unified real-time three-dimensional scene model, again by intelligent early warning decision engine layer carries out scene reasoning and risk assessment, realizes the active early warning and automatic linkage of risk Disposal, finally through cloud management application layer carries out global visual display and is based on historical data self-learning optimization operation strategy;The application utilizes the closed loop architecture of multilayer cooperation, realizes the whole process intelligent management from real-time perception, accurate understanding to automatic decision and continuous optimization to physical warehouse, significantly improves the safety, efficiency and self-level of warehousing operation.

This application discloses an application data migration method. In this method, a cloud management platform can be used to forward first data from a first device to a target device, thereby migrating the application data of the first device. This allows users to restore the data state of a target account in a first application on the target device as needed. Because the first data is transmitted based on the cloud management platform, it can be easily distributed to different devices, thus enabling application data migration at different times and locations, no longer limited to application data migration within the same space.

This invention discloses an integrated intelligent control system for pathogen aerosol monitoring and disinfection, relating to the field of pathogen aerosol control technology. Based on a "front-end sensing—edge control—cloud management" architecture, the system collects pathogen aerosol and environmental parameters in real time through monitoring devices, while disinfection devices perform disinfection tasks. Relying on multi-network communication guarantees, closed-loop control logic, and multi-terminal collaborative management, it achieves functions such as real-time monitoring of pathogen aerosol concentration, adaptive adjustment of disinfection dosage, and remote intelligent control, realizing deep linkage between monitoring and disinfection devices. This system is suitable for public health prevention and control in densely populated places such as hospitals, airports, and shopping malls, and can significantly improve the accuracy, efficiency, and intelligence level of pathogen aerosol disinfection.

The present application provides a kind of crane hoist area personnel intrusion identification method, comprising the following steps: S1, video image is collected;S2, video image is preprocessed;S3, the division of dangerous area is completed;S4, extract foreground moving target in video frame;S5, target detection is carried out to video frame;S6, measure real-time relative distance;S7, confirm effective personnel target;S8, confirm risk level;S9, execute hierarchical early warning linkage control.The present application also provides a kind of crane hoist area personnel intrusion identification system, based on the crane hoist area personnel intrusion identification method described above, comprising video image acquisition module, AI image processing module, edge computing module, early warning linkage module and cloud management module.The present application solves the technical problems that the existing crane hoist area safety protection mode is difficult to adapt to complex hoisting conditions and has low precision, and produces the technical effects of improving the response capability to complex operating environment and improving the detection precision.

The present application relates to the technical field of automobile sharing management, and provides an online management system for multi-family shared cars to solve problems such as frequent reservation conflicts and low scheduling efficiency when multiple families share cars. The system includes a family user end module and a cloud management platform module, which are connected through wireless network communication. The family user end module supports operations such as family user reservation application, information display, identity verification, and use feedback. The cloud management platform module has functions such as data storage, reservation scheduling, authorization management, operation and maintenance management, and cost settlement, and can realize reservation scheduling, use monitoring, and full-process management of shared cars by multiple families, and can meet the needs of multiple families for cars in a standardized and efficient manner.

The present application is suitable for the field of intelligent agricultural technology, and provides a tea garden precision fertilization closed-loop system based on multispectral imaging and environmental response, comprising: a data acquisition subsystem that acquires multispectral data, environmental sensor data and weather forecast data of the tea garden in real time; a data processing and analysis subsystem that inverts the nutrient content and calculates the influence coefficient of temperature on the fertilizer decomposition rate, the influence coefficient of humidity on the root absorption efficiency and the predicted loss amount; a fertilization decision subsystem that comprehensively considers the nutrient gap, the influence coefficient and the predicted loss amount, and calculates the corrected fertilization amount and the target fertilization time window in combination with the weather forecast, generates a variable fertilization prescription map; a fertilization execution and feedback subsystem that executes zoned variable fertilization and re-measures the multispectral data to evaluate the effect; and a cloud management platform that realizes data storage, visualization and alarm. The present application effectively improves the accuracy of fertilization decision and the fertilizer utilization rate, and realizes the precision and intelligence of tea garden fertilization.

This invention discloses an intelligent hydrological and water resources monitoring system based on the Internet of Things (IoT), belonging to the field of hydrological and water resources monitoring technology. It includes an intelligent monitoring terminal, an edge computing gateway, and a cloud management platform. The intelligent monitoring terminal uses LoRa+NB-IoT dual-mode communication technology to achieve real-time and automatic acquisition of hydrological data across the entire watershed. A solar power unit meets its continuous operation needs in environments without mains power. The edge computing gateway performs local cleaning, threshold judgment, and compression processing on the acquired data, improving data accuracy and reducing network transmission costs. A breakpoint resume function ensures data integrity. The cloud management platform stores, classifies, and visualizes the data, allowing managers to intuitively grasp the hydrological and water resources status of the watershed. This system has the advantages of comprehensive monitoring coverage, real-time and accurate data, convenient deployment and maintenance, and timely early warning, providing reliable data support for water resources management decisions.