41 results about "Service cloud" patented technology

The embodiment of the invention provides a resource configuration method, a resource configuration device, electronic equipment, a chip, a storage medium and a computer program product. The resource configuration method comprises the steps of collecting terminal side user data and service cloud side node data; and based on the terminal side user data and the service cloud side node data, configuring network resources for the terminal side user.

A system can include one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations. The operations can include connecting an edge device located at a vehicle service site to a centralized vehicle service cloud platform. The edge device can execute a site controller application to manage operations at the vehicle service site. The operations also can include configuring one or more IoT devices located at the vehicle service site to capture monitoring data. The operations further can include receiving the monitoring data for usage by the site controller application. The operations also can include receiving a service request for a vehicle. The operations also can include generating and dynamically updating a schedule for the vehicle service site. Other embodiments are disclosed.

Provided are a method, a system, and a storage medium for determining a demand level of service information. The method includes: obtaining first sensor information of a first production line; determining, based on the first sensor information, a candidate push object and a push demand value of the candidate push object; determining a target push object based on the push demand value; determining reference information of the target push object based on the first sensor information, and sending the reference information to an IIoT user platform corresponding to the target push object; in response to receiving a recommended demand, generating a recommended production parameter and / or a recommended monitoring parameter based on the reference information, and sending the parameter(s) to the IIoT user platform corresponding to the target push object to obtain confirmation information; and generating, based on the confirmation information, an adjustment instruction.

The invention belongs to the technical field of network cloud authentication, and relates to an SRv6-based network cloud authentication method, storage medium and device, and the method comprises the steps that a network client sends an SRv6-based network authentication request message to a network management cloud through a basic network; after receiving the SRv6-based network authentication request message, the network management cloud replies an SRv6 path packet to the network client initiating the request message; after receiving the SRv6 path packet, the network client processes the identity authentication information and sends the processed identity authentication information to the network service cloud; the network service cloud authenticates the identity authentication information, if the authentication succeeds, the network client accesses the network service cloud, and if the authentication fails, the network client does not access the network service cloud; according to the method provided by the invention, the identity authentication information of the network client is divided into a plurality of parts and is sent to the network service cloud through a plurality of paths, so that the sub-identity authentication information is forwarded according to different paths, and line repetition is effectively avoided.

The application discloses a kind of collaborative robot system and service process for active power grid marketing, belong to artificial intelligence and electric power marketing service technical field.System includes: robot perception interaction end, cloud intelligent analysis hub and dynamic customer memory bank, robot perception interaction end deploys lightweight vision model, real-time identification customer emotion, body state and explicit feature, and initiatively trigger service;Cloud intelligent analysis hub uses power grid knowledge enhanced large language model, carries out depth demand analysis and individualized strategy generation to multi-modal data;Dynamic customer memory bank stores customer historical interaction record and portrait information in the form of knowledge graph, realizes the continuity and memory of service.The application is through edge small model+cloud big model collaborative architecture, general AI capability and power grid business knowledge are deeply fused, so that robot can actively identify customer demand, provide marketing service, improve customer experience and marketing conversion rate of electric power business hall.

The application discloses an intelligent pipe cooling circulation control system and method based on ship lock construction, which comprises the following steps: dividing a ship lock construction structure into A pipe cooling circulation control subareas; covering the A pipe cooling circulation control subareas by B cooling circulation pipelines; receiving multi-dimensional data of each pipe cooling circulation control subarea by each edge key control node, and transmitting the data to a cloud cooling control service; after receiving the data, the cloud cooling control service generates A cooling circulation load demand risk coefficients based on a first deep learning algorithm; if it is judged that at least one of the A cooling circulation load demand risk coefficients is at risk, then the B cooling circulation pipelines are subjected to pipe cooling circulation control based on a second algorithm, and a PID control algorithm is used to adjust the cooling water flow and the cooling water temperature of the pipelines; the application realizes precise pipe cooling circulation control adjustment, improves the ship lock construction quality and reduces the risk of concrete hardening cracking through deep learning algorithm prediction and monitoring and the introduction of an unmanned aerial vehicle for the inspection of the outer surface of the cooling pipe.

The application discloses a lithium battery energy storage station cloud-edge collaborative intelligent fire-fighting linkage system and an implementation method. It comprises a fire service cloud platform system, a network layer, a sensing layer and a control layer. The sensing layer reports various data in real time. The network layer extracts a feature vector set to construct an effective feature parameter identification classifier. The control layer realizes comprehensive linkage fire extinguishing control. The fire service cloud platform system is used for processing data logic of a program and is responsible for accessing data in a database. The application has the beneficial effect that a plurality of operating state parameters representing lithium batteries of an energy storage station are preprocessed on an edge gateway side, such as feature extraction, statistical analysis, dimension reduction optimization and the like, and then trained and dynamically identified through an improved BP neural network model deployed in an intelligent fire service cloud platform. According to the identification result, early warning information is sent out. In combination with a fire-fighting linkage control system, a complete cloud-edge collaborative intelligent fire-fighting linkage control method is formed, so that the operating safety risk is greatly reduced.

Disclosed herein are system, method, and computer program product embodiments for identifying and removing orphan data in a Database-as-a-Service (DBaaS) cloud computing platform. In embodiments, a workflow is executed that accesses an event service database of the platform to obtain a list of deleted customer entities, queries a control plane of the platform to obtain a list of existing DBaaS instances, determines that a particular existing DBaaS instance is associated with a particular deleted customer entity, identifies the particular existing DBaaS instance as a potential orphan DBaaS instance, validates that the particular existing DBaaS instance is an orphan DBaaS instance, and in response to validating that the particular existing DBaaS instance is an orphan DBaaS instance, performs one or more of generating an alert that identifies the particular existing DBaaS instance as an orphan DBaaS instance or removing the particular existing DBaaS instance from the DBaaS cloud computing platform.

The invention discloses a highway networking charging management and information resource wide-area fusion scheduling system, relates to the technical field of intelligent traffic charging management, and constructs a highway networking charging management architecture with multi-level management from top to bottom in a management area, and establishes mutual access channels through a cloud service network. The global center management node supervises the working state of each resource scheduling management node, overall plans business cooperation among the resource scheduling management nodes according to the working state, and issues a scheduling instruction to each resource scheduling management node; the resource scheduling management nodes are mutually standby nodes, the corresponding toll lane systems and cloud seats are managed according to scheduling instructions, a road network resource scheduling management network is generated and maintained, the toll lane systems provide services for users passing through toll lanes of a toll plaza, and the cloud seats are used for remotely receiving and processing manual service requests. Through cross-regional scheduling and multi-warehouse mutual backup of the human resources, comprehensive clouding and unified scheduling of the computing resources and the human resources are realized.

The invention relates to the technical field of network communication, and provides a secure access service edge fusion method and device. According to the invention, a VXLAN tunnel is constructed between a service cloud gateway and an LAN port of SD-WAN vCPE; the branch terminal sends the original message to the access cloud gateway; the access cloud gateway forwards a first message obtained based on the original message to the service cloud gateway; the service cloud gateway converts the first message into a second message, so that the second message is forwarded to the SD-WAN vCPE through the VXLAN tunnel; and the SD-WAN vCPE processes the received second message to obtain a third message, and forwards the third message to headquarters equipment, so as to transmit the traffic of the branch terminal to the headquarters equipment, thereby solving the problems of low efficiency, high cost and complex configuration of the existing remote networking scheme, or large data transmission quality fluctuation caused by strong dependence on a public network.

The present disclosure provides a cloud application processing method and device, electronic equipment and storage medium, relates to the technical field of computers, in particular to the field of cloud application, cloud service and cloud computing. The specific implementation scheme is: in response to detecting that an activation operation for multiple cloud applications is triggered, encrypting binding information corresponding to the multiple cloud applications to obtain first encrypted information. The binding information includes first certificate information and hardware identification information of a first client; sending the first encrypted information to a server, so that the server decrypts the first encrypted information to obtain first decrypted information; in response to receiving second encrypted information from the server, decrypting the second encrypted information to obtain second decrypted information. The second decrypted information includes verification success information and activation information; in response to detecting the verification success information, completing the activation operation for the multiple cloud applications by using the activation information, so that the first client performs multi-opening operation for the multiple cloud applications.

This invention proposes a method for optimizing mobile social security services based on a distributed and microservice architecture. Its technological breakthroughs are manifested in three core aspects: Elastic Service Cloud Network: Based on the self-developed PDFC framework, Spring Cloud microservice architecture, and Kubernetes containerization technology, microservices are deployed in a split manner, enabling dynamic scaling of microservice container nodes and second-level fault self-healing. Intelligent Data Hub: A cross-domain data channel is built based on Apache Kafka, collecting social security business data and health record data in real time with millisecond-level transmission efficiency. Intelligent Reporting Engine: An innovative three-dimensional intelligent reporting system is constructed. Pre-event reports are generated by parsing physical examination information; during-event reports are generated through dynamic monitoring of risk warnings; and post-event reports are generated based on actual business processing, achieving an upgrade and transformation of the governance model from "people seeking services" to "services benefiting people."

A data storage method and apparatus, and a computing device are provided. The method includes: in a process in which the first node processes a plurality of access requests, locally storing or caching hot data in the first node, migrating cold data to a cloud storage service, and locally storing or caching metadata of the cold data in the first node, where the cloud storage service is a service deployed by a cloud computing platform in a cloud computing resource, the cloud computing platform deploys a cloud database system in the cloud computing resource managed by the cloud computing platform, the first node is a primary database node or a secondary database node of the cloud database system, the hot data and the cold data are different data tables of the database or different table partitions of the data table, and the hot data and the cold data are determined based on either or both of a quantity of times and a data amount of accessing a table partition of a data table. According to the method, data storage costs can be reduced without affecting performance.

The invention relates to a large-scale wireless network automatic test system and method, the system comprises a test tool, a tested device, a business cloud and a mechanical arm, the test tool and the tested device are respectively in communication connection with the business cloud and the mechanical arm, the test tool is used for determining a control instruction according to a pre-configured test case, and the control instruction is sent to the tested device. Controlling the tested equipment through a transparent transmission interface or a mechanical arm of the business cloud based on a control instruction, wherein the control instruction is an instruction irrelevant to a protocol; and the test tool is also used for acquiring a device state returned by the tested device in response to the control instruction through the service cloud, judging whether the device state is consistent with the control instruction, if so, executing the next test case until all test cases are executed, and outputting a test report.

The invention discloses a Photoshop-embedded AI image generation system and method, and relates to the technical field of AI image generation and design tool integration. The system comprises a key management module, an LAVIE PS plug-in module, a user binding tracking module and a cloud AI image generation service module. The method comprises the following steps: generating an access key with a fixed limit through a key management module; a user inputs a secret key through the plug-in embedded with the Photoshop and verifies the secret key; after the verification is passed, generating parameters are set and sent to the cloud service; the cloud calls the AI model to generate an image and returns to the plug-in for loading; and meanwhile, the tracking module records the use log and updates the quota. According to the method, seamless integration of an AI generation function and a design process is realized, the efficiency is improved, the problems of resource abuse, operation non-traceability and key security management are effectively solved through binding of the key quota and the user, and the method is particularly suitable for commercial AI image generation services.

The invention discloses a biological voucher processing system and a biological voucher processing method, which are used for solving the problems that the service timeliness cannot be met and the scene adaptation is poor due to processing delay in the prior art. The biological voucher processing system comprises a voucher management service, and an intermediate service, a cloud storage and an equipment management service which are respectively connected with the voucher management service. The device management service is connected with at least one device; receiving the to-be-processed image from the certificate management service through the intermediate service, and performing synchronous matting on the to-be-processed image to obtain a processed image; receiving the processed image returned by the intermediate service through the certificate management service, encrypting the processed image, and transmitting the encrypted image to the cloud storage; and receiving voucher data generated by the voucher management service through the device management service, determining a target device based on the voucher data, and issuing a voucher to the target device according to the voucher data, so that the target device obtains the encrypted processed image from the cloud storage.

The application discloses a method and a gateway device for joint debugging test, and relates to the technical field of terminals. The method solves the problem of low test efficiency of the gateway device during joint debugging test when the service cloud platform switches the running environment during the test and production stages. The method comprises the following steps: after a first gateway device is reset, the first gateway device establishes a connection with an access cloud platform, the access cloud platform stores a corresponding relationship between the device identifier of at least one gateway device and the address of the service cloud platform under at least one running environment, and the at least one gateway device comprises the first gateway device. The first gateway device obtains the address of the first service cloud platform corresponding to the device identifier of the first gateway device from the access cloud platform. The first gateway device establishes a connection with the first service cloud platform according to the address of the first service cloud platform. The first gateway device performs joint debugging test with the application of the user device through the first service cloud platform.

The utility model provides a one-key dialing and remote landing calling system, the dialing and remote landing calling system comprises elevator equipment, a dialing Internet of Things module, a cloud platform, a user terminal and a rescue terminal, the dialing Internet of Things module is connected with a control system of an elevator, the dialing Internet of Things module is connected with the cloud platform through networking, and the user terminal is connected with the rescue terminal through the cloud platform. The cloud platform at least comprises a terminal server, the cloud platform provides elevator calling service for the user side, the cloud platform provides rescue information for the rescue side, and the user side and the rescue side transmit and receive signals and control an elevator through the terminal server. The dialing Internet of Things module is connected with elevator equipment, signals of an elevator and operation function signals of a user are concentrated on the dialing Internet of Things module, the dialing Internet of Things module is in communication connection with the cloud platform, and the cloud platform provides elevator calling function service and rescue function service, provides program processing capacity and rapidly sends processing results to all terminals.

Technologies of a device-based Fast Presence Detection (FPD) for a contactless sleep-tracking device are described. One method of a sleep-monitoring device includes receiving radar data from a radar unit. The radar data includes i) first data representing a breathing waveform associated with a user, ii) a first set of range values, and iii) a first set of confidence values associated with the first data. The method determines absolute magnitude values, first infinite impulse response (IIR) values using the first set of range values, and second IIR values using the first set of confidence values. The method determines a first event representing the user located in a first region using the absolute magnitude values and the first and second IIR values. The method sends an indication of the first event to a cloud service that causes one or more devices in the environment to perform one or more actions.

The present document describes systems and methods for on-device person recognition and provision of intelligent alerts. The system includes a decentralized multi-camera system for on-device facial recognition. A device (e.g., security camera, video doorbell) captures images / video of a person, processes input image frames, detects face images, filters static faces, and aligns a rotation of the face to be upright and frontal. The device then filters low-quality face images and / or images having a large portion of the face occluded. The device computes a face embedding, compares it against a set of locally stored reference embeddings, and sends matching results to cloud services, which, based on the matching result, notifies the device owner whether the observed person is a known person or a stranger. Face detection and recognition computations are performed on device, not at the cloud. No sensitive information is transmitted off device and privacy is thus preserved.

The invention discloses an APK operation compliance verification method and system based on cloud policy control. A client verification module is embedded in an application, environment feature information representing a running environment is collected in the starting and running stages of the application, and the information is encrypted and sent to a cloud verification service; the cloud verification service performs matching analysis on the operation environment based on a pre-configured strategy rule to generate a corresponding verification control instruction; and the client verification module performs runtime control on the display process or process state of the application according to the verification control instruction. The verification logic and the strategy rule are intensively maintained by the cloud and can be dynamically updated, and the client only executes the cloud instruction, so that the effective verification of the compliance use of the APK is realized, and the application is prevented from being used in an unauthorized operation environment.

Techniques for universal data transmission to multiple cloud storage platforms are described. A universal data transmission system includes a data integration framework, a set of serializers, a plurality of authenticators, a plurality of transports, and a cloud connection service. The cloud connection service is capable of loading the data from an on-premise device to each of the plurality of cloud storage platforms. The cloud connection service receives a selection of a cloud storage platform for the cloud connection service to load the data and configures a plurality of channels based on the category of the collected data and the selected cloud storage platform to a specific configuration. The cloud connection service selects a specific serializer, a specific authenticator, and a specific transport, which are pluggable to form the transmission route connecting the on-premise device to the selected cloud storage platform.

A data storage method and apparatus, and a computing device are provided. The method includes: in a process in which the first node processes a plurality of access requests, locally storing or caching hot data in the first node, migrating cold data to a cloud storage service, and locally storing or caching metadata of the cold data in the first node, where the cloud storage service is a service deployed by a cloud computing platform in a cloud computing resource, the cloud computing platform deploys a cloud database system in the cloud computing resource managed by the cloud computing platform, the first node is a primary database node or a secondary database node of the cloud database system, the hot data and the cold data are different data tables of the database or different table partitions of the data table.

The cloud management system is configured to manage an infrastructure on which a first service of a first tenant and a second service of a second tenant are configured. The cloud management system obtains an authorization request of the first tenant which includes a tenant identifier of the second tenant, an authorization name, and a permission for the second service to invoke the first service. The cloud management system creates the permission based on the authorization request; obtains a permission obtaining request that is inputted by the second tenant and that includes the authorization name and a tenant identifier of the first tenant, configures, based on the permission obtaining request, the second tenant to obtain the permission; and allows, based on the permission when the second tenant configures the second service to invoke the first service, the second service to invoke the first service.

In various embodiments, systems and methods for ledger-based cookie management are provided. Rather than store cookie data as text files on the local device drive, cookie data is recorded to a blockchain technology cookie ledger store on a network resource. When a client application (e.g., a browser) on the UE is directed to a cloud-based service, and that cloud-based service calls for access to a cookie, that call is processed by a cookie gateway executing on the UE. The cookie gateway may verify authenticity of the user and generate a cookie access token that it transmits to the cloud-based service. The cloud-based service may use the cookie access token to locate the cookie ledger and access one or more records storing cookie data used by the cloud-based service. The cookie access token may expire upon termination of the session between the user equipment and the cloud-based service.

Systems and methods for integrating machine learning models are provided, and more specifically, platforms as a service (PaaS) cloud are used to predict the probability of an operator's success in an environment. An embodiment includes a system comprising: a processor executing computer-executable components stored in memory; a trained machine learning model predicting the probability of successful deployment of an operator in an environment having a namespace of a platform as a service (PaaS) cloud; and a deployment component receiving a first operator and a first namespace, and employing the trained machine learning model to predict the success of deployment of the first operator in the first environment.

The present invention provides a mobile vehicle management device capable of suitably acquiring statistical data regarding the vehicle's status in relation to the process it has instructed to execute. [Solution] The vehicle cloud server 30 receives upload data UD2, which is a reception result indicating that the in-vehicle terminals 20 of multiple vehicles were able to successfully receive the job request JR2, and counts the number of inactive vehicles, which is the number of vehicles that were able to successfully receive the job request JR2, based on the upload data UD2. The vehicle cloud server 30 also receives upload data UD2 in which the number of active transitions of the job is one or more, and counts the number of active vehicles and the total number of active vehicles, which represent the number of vehicles that sent the upload data UD2 and the total number of vehicles. The vehicle cloud server 30 then sends upload data UD1, which includes information on the number of inactive vehicles, the number of active vehicles, and the total number of active vehicles, to the service cloud server 40.

The invention provides a mirror image downloading method and a mirror image downloading management system for terminal equipment, and the method comprises the steps: responding to a detected operation instruction for entering a Fastboot mode, and driving the terminal equipment to enter the Fastboot mode; the terminal equipment is accessed to an authorization management platform, a to-be-authorized data packet is sent to the authorization management platform, the authorization management platform comprises a local tool server and a cloud authorization server, the local tool server is suitable for providing signature service for the to-be-authorized data packet, and the cloud authorization server is suitable for providing signature service for the to-be-authorized data packet; the cloud authorization server is suitable for providing signature verification service for the to-be-authorized data packet signed by the local tool server, and performing authorization decision according to a signature verification result and a terminal verification strategy; responding to a received authorization success response returned by the authorization management platform, and accessing the terminal equipment to the burning tool platform; and downloading a mirror image file corresponding to the terminal equipment from the burning tool platform.

The invention discloses an anti-explosion intelligent relief food container type vending machine based on new energy and face recognition. The invention discloses an anti-explosion intelligent relief food container type vending machine which integrates an anti-explosion container, face-scanning quantitative receiving, wind and light storage and power supply and a satellite communication relief food distribution system. According to the system, the safety of equipment is guaranteed through an anti-explosion and anti-smashing wall version container structure with a three-layer protection structure, the situation that photos / videos are falsely claimed is prevented by adopting a multispectral living body verification technology, and food distribution objects are linked with a data interaction cloud platform system and a background service cloud platform of a control center through face recognition and face scanning. Precise quota management is achieved in combination with a government big data platform, a temperature control storage module is arranged in the system and can store various kinds of food, a wind-solar complementary power supply system ensures stable operation, and Beidou satellite communication ensures data transmission in an extreme environment.

The invention discloses a home nursing service cloud side collaborative management method and system, and the method comprises the steps: carrying out the integrity verification of nursing request data, recognizing a transmission abnormal section, and carrying out the priority packaging according to the emergency degree of data related to the abnormal section; performing weighted evaluation by integrating the geographic coordinates of the nursing personnel and the real-time load state to screen an optimal service node, and establishing a downlink push channel to transmit task information; the edge side caches task data to form a local mirror image, and supports off-line service execution and nursing record retention in a weak network environment; identifying synchronous interruption through link detection and activating a breakpoint resume strategy, and performing conflict pre-detection on unsynchronized data to screen out a safe section to construct recovery configuration; and determining a confirmation node based on the time delay distribution of the synchronization progress, and executing bidirectional response verification to complete cloud edge data synchronization. The method adapts to the network fluctuation characteristics of the home scene, and can guarantee the priority response of the nursing request and the reliable transmission of the service data.