51 results about "System deployment" patented technology

The application discloses a live broadcast marketing recommendation system and method based on user portrait, relates to the technical field of data processing, and aims to solve the problems of lack of intelligent identification of user interest and consumption behavior, serious homogenization of recommendation and low conversion efficiency in the existing live broadcast marketing mode. The system is deployed in the live broadcast platform background service cluster, and the overall architecture includes a user portrait collection module, a behavior analysis engine, a marketing recommendation module, a real-time push component, an interest label visualization module and an automatic optimization mechanism. Each module realizes data interaction through a high-speed internal network and a message queue, and establishes a real-time connection with the front end and the platform transaction database. The system realizes the precision, personalization and intelligent upgrading of live broadcast marketing, effectively improves the recommendation conversion efficiency, reduces the loss of high-value users, enables the precise operation of anchors, optimizes the user experience and the platform competitiveness, and has significant technical value and commercial value.

The system obtains an issue associated with a network and resolves the issue by suggesting a solution and receiving an approval from an AR / VR device. Based on the issue, the system creates a ticket describing the issue and obtains diagnostic information associated with the issue. Based on the diagnostic information, the system determines a fix for the issue and sends a first notification to the AR / VR device. The first notification includes a description of the issue, the fix for the issue, and a request to test the fix. Upon receiving an approval to test the fix, the system performs regression testing using the fix and determines whether the fix passed the regression testing. Upon determining that the fix passed the regression testing, the system sends a second notification to the AR / VR device requesting an approval to deploy the fix, and upon receiving the approval, the system deploys the fix.

This invention discloses a method for optimizing the operation of a wind-solar hydrogen production system based on hierarchical verification deep reinforcement learning, belonging to the field of new energy hydrogen production system operation optimization technology. The method includes: collecting environmental and equipment information to construct a system state vector; establishing a multi-agent framework based on the soft actor-critic algorithm, defining the energy storage battery and electrolyzer as independent agents, and outputting control commands through continuous-discrete hybrid actions. Before execution, a Level I safety verification is performed, and the state is updated after passing; a fusion reward is calculated based on the new state using a global-local fusion reward mechanism. State samples are stored in an experience buffer for network parameter updates. During training, a Level II model performance verification is periodically performed, and qualified models are included in the candidate set; after training, a Level III deployment verification is performed, and the optimal model is selected for use in the actual system. This invention improves the operational efficiency, equipment lifespan, and system deployment reliability of wind-solar hydrogen production systems under fluctuating environments.

The application relates to the technical field of knowledge question answering, in particular to a knowledge question answering method based on a multi-modal document understanding large model of a graph structure, which comprises the following steps: obtaining a target task and a target document graph corresponding to the target task; generating a target heterogeneous document graph corresponding to the target document graph according to the target document graph; inputting the target task and the target heterogeneous document graph into a preset large model to obtain a target question and answer text corresponding to the target task; the method can achieve higher accuracy and robustness on multiple public benchmark tasks (such as document question answering, graph table question answering and table understanding); the method has excellent generalization ability for novel and complex document layouts; and the method realizes more simple and efficient system deployment and application through an end-to-end unified architecture.

The application discloses an intelligent voice alarm system and method suitable for a power monitoring system, which comprises multiple functions of alarm event level definition, voice broadcast mode, specified area alarm mode, temporary shielding object, alarm event confirmation, mute function, voice broadcast sequence, voice text replacement, voice broadcast configuration, voice file configuration and system self-defined configuration; the system comprises an alarm event management module, a broadcast control module, a voice output module and a configuration management module; the alarm event management module generates an alarm to be broadcast according to alarm event level definition information and stores the alarm into a cache queue; the broadcast control module generates a voice broadcast request according to the voice broadcast sequence and the voice broadcast mode; and the voice output module receives the request and performs voice synthesis and broadcast. The application realizes fine control of the whole process of the alarm event through a modular architecture, supports deployment of a Windows system and a Linux system, and has high flexibility, expandability and cross-platform compatibility.

The invention discloses a control system deployment method and device, equipment and a storage medium, and the method comprises the steps: determining at least one to-be-deployed physical equipment in a target control system according to a subsystem of the target control system, and determining a data communication protocol between different physical equipment according to the equipment type of the physical equipment, generating an equipment topological structure; determining at least one system function block corresponding to a subsystem based on system function requirements of different subsystems in the target control system, and generating a function block topological structure based on a function logic relationship between the system function blocks; and determining a system deployment model of the target control system based on the equipment topological structure and the functional block topological structure. According to the technical scheme, the system logic structure of the target control system is optimized, and the association degree between different subsystems is improved.

The application discloses a BMS parallel machine addressing method, device, equipment, storage medium and product, relates to the technical field of battery management system, and the method comprises the following steps: sending an initialization instruction to a BMS module, so that the BMS module enters a waiting addressing state; determining a host unit from the BMS module, and allocating a host address to the host unit; sending an addressing instruction to the host unit, so that the host unit generates a coding signal containing the host address; sequentially transmitting the coding signal among the remaining BMS modules, and taking the BMS module receiving the coding signal as a slave unit; and based on an address allocation rule and the coding signal, sequentially allocating corresponding slave addresses to each slave unit. Compared with the existing manual code dialing mode, the application realizes dynamic address allocation by automatically generating and sequentially transmitting the coding signal, thereby realizing full automation of the addressing process, effectively avoiding address conflicts, and significantly improving system deployment efficiency and scalability.

The application discloses a kind of tunnel surrounding rock integrity offline evaluation method and intelligent agent system, first acquire tunnel face multi-modal original data, utilize cloud large multi-modal model distillation to obtain lightweight local language model and lightweight visual model;Intelligent agent scheduling engine is constructed to realize the unified task scheduling and data flow of each functional module, and the system is deployed in edge computing device;When running offline, image semantic segmentation, feature parameter extraction, engineering report analysis, multi-modal fusion reasoning are sequentially completed by intelligent agent scheduling engine, and the surrounding rock integrity grade prediction result and supporting construction suggestion are automatically output, so that the end-to-end unified fusion analysis of image, text, numerical multi-modal information can be realized under weak network / disconnected network environment in tunnel site, while having missing data degradation prediction ability and online incremental continuous optimization ability, which significantly improves the automation degree, result consistency, environmental robustness and engineering applicability of tunnel surrounding rock integrity evaluation.

This invention belongs to the field of multi-power uninterruptible power supply and distribution technology, and discloses a novel fast switching circuit, a fast power switching system, a fast switching STS cabinet, and a control method. The core improvement is the inclusion of local operation switching interlocking logic, employing a four-level redundant control power supply architecture with dual-path interlocking, UPS, and DC conversion. Power switching time is ≤8ms, supporting local / remote dual-mode control and seamless integration with the upper-level EMS system. This invention completely eliminates the risk of accidental switching during operation and maintenance, achieving equipment reliability of over 99.999%, improving electromagnetic interference resistance by 65%, and reducing system deployment costs by 32%. It can be widely applied in scenarios with high power supply continuity requirements, such as integrated industrial and commercial power storage, data centers, industrial power distribution, and microgrids.

This invention relates to the field of autonomous driving technology and discloses an edge-assisted UAV cooperative adaptive bird's-eye view perception method and system. The method includes: acquiring video frames of a road scene and extracting semantic regions of interest (ROIs); fusing the spatial ROIs with the semantic ROIs to obtain a fused ROI; the UAV performs differential processing on the video frames based on control parameters and the fused ROIs, encodes the processed video frames into a video stream, and uploads it to an edge server; the edge server decodes the video stream, performs a bird's-eye view perception task, updates the spatial ROI based on perception performance, and determines the control parameters for the next moment to adjust the differential processing and encoding of the video frames for the next moment; this method utilizes the UAV's aerial view advantage to acquire road scene video and performs the main bird's-eye view perception calculations on the edge server, reducing the computational burden on the UAV and improving the feasibility of system deployment.

The application relates to the technical field of computer edge computing, and discloses a production equipment abnormality monitoring and self-adaptive control method based on real-time edge computing. The method comprises the following steps: collecting equipment operation, process, environment and maintenance data through a multi-source sensor; performing data preprocessing and multi-scale feature extraction on the edge side; realizing millisecond-level abnormality detection by using a lightweight neural network; positioning an abnormality source by combining a Bayesian causal diagram reasoning engine; and generating optimal control parameters based on a self-adaptive control strategy library or online reinforcement learning, and issuing the optimal control parameters to a PLC for execution. The system is deployed on an edge computing node, and the control loop delay is ensured to be no more than 10 milliseconds. The application realizes the collaborative control of high robustness, self-adaptability and energy efficiency optimization, and significantly improves the product qualification rate, reduces energy consumption and unplanned downtime.

The application discloses an automobile part intelligent mistake-proofing system and method based on AI vision and real-time data interaction. The system is deployed at an artificial assembly station and is used for preventing mixed assembly errors of multiple appearance-similar variant parts in the same function category. An appearance image of a non-identified part is directly collected by a vision collection unit, and a built-in deep learning model is used to identify the visual feature category of the part. The deep learning model is used to identify the intrinsic feature of the part. Meanwhile, vehicle VIN and station information are acquired in real time, standard assembly requirements are dynamically queried, and cross comparison is performed. If the information is inconsistent, physical blocking, sound and light alarm and remote alarm are triggered immediately. The application significantly improves the mistake-proofing accuracy and reliability, can be perfectly matched with the production line rhythm, and has high system integration and compatibility.

The application discloses a kind of based on big language model's molecular sieve vertical field intelligent system construction method, its characteristics are that the method includes: structure data standardization and literature information extraction, inject field knowledge and tool call specification by supervision fine tuning, carry out reinforcement learning training using GRPO group relative strategy optimization algorithm and multidimensional reward function, construct GNN graph neural network agent model, realize millisecond level property prediction and uncertainty quantification, and system deployment based on asynchronous scheduling and multistage cache etc. steps.Compared with the prior art, the application has the functions of knowledge question and answer, property prediction, reverse design and synthesis planning in the field of molecular sieve, the monomer big language model internalizes professional knowledge through deep field training, uses GNN agent model as the reward signal source of reinforcement learning to greatly improve the training efficiency, balances response speed and calculation accuracy using native Function Call capability, the method is innovative, the system is complete, and has a broad prospect of material research and application.

This application discloses a bidirectional communication system and method for board daisy chain based on a single-wire protocol, relating to the field of computer technology. This application constructs a single-bit serial protocol daisy chain system without an independent clock line, employing dual single-wire directed links or a single half-duplex shared link to achieve bidirectional transmission between boards. This significantly reduces the hardware connection harness and input / output resource usage, lowers connector and line costs, and is suitable for scenarios involving large-scale, low-cost board cascading. After power-on, master-slave identification is automatically completed based on the upstream valid frame reception status, avoiding conflicts between multiple master nodes without the need for preset DIP switches, configuration files, or external addressing commands. The motherboard uses a preset default address, and the slave boards use an allocation method where the upstream address is incremented hop by hop, ensuring a strict correspondence between physical cascading positions and logical addresses. This achieves automatic convergence with zero manual address configuration, improving system deployment and maintenance efficiency.

The utility model belongs to the field of industrial computer, concretely relates to front -positioned control knob industrial computer, including sheet metal middle frame, aluminium alloy front panel and aluminium alloy integrated back cover, sheet metal middle frame is installed in aluminium alloy front panel and is inserted with touch panel, touch panel adopts capacitive multi -point touch control technology, response time is below human body perception threshold value, supports zoom, rotation and drag gesture operation, the back of aluminium alloy front panel can detachably install sheet metal front frame. The utility model discloses through adopting capacitive touch technology, make touch operation more sensitive, smooth, and user can control through finger touch or pen touch, and support multi -point touch, and user can carry out multi -point touch simultaneously, such as zoom, rotation, drag and so on gesture, touch response time is extremely short, far below human body perception time, improve equipment use experience, touch panel built -in intelligent control module supports power -on automatic starting, timing switch, USB control, network wake -up, remote batch system deployment and multi -band wireless communication function.

The application relates to the technical field of industrial monitoring, in particular to an industrial monitoring visual browser implementation method based on a Qt framework, which realizes core characteristic functions similar to general browsers based on the Qt framework, centrally controls visual content, and is responsible for industrial equipment data collection, analysis, storage and instruction forwarding, and also undertakes unified control and update of the visual content; the client only serves as a visual browser terminal and is responsible for data reception and picture rendering, does not need to participate in the logic processing of the visual content, realizes browser-type control effects of service end modification and client synchronous display, relies on Qt native cross-platform and graphic rendering capabilities, only serves as a terminal to complete data reception and picture rendering, realizes low-delay data interaction by combining a self-defined binary communication protocol, supports Windows, Linux, embedded and other multi-system adaptation, significantly reduces system deployment and maintenance costs, and can be widely applied to various industrial real-time monitoring scenes.

This application provides a cloud platform storage system, method, device, and medium, relating to the field of cloud platform technology. The cloud platform storage system includes a compute node cluster and a storage node cluster. The compute node cluster includes multiple compute nodes, and multiple disks on these nodes constitute a MinIO object storage cluster for storing image resources and / or cloud disk backup resources. The storage node cluster includes multiple storage nodes, and multiple disk arrays on these nodes constitute an NFS storage cluster for storing cloud disk resources. The compute node cluster stores cloud disk resources in the NFS storage cluster through a cloud disk service, stores cloud disk backup resources in the MinIO object storage cluster, and stores image resources in the MinIO object storage cluster through an image management service. This approach meets the storage needs of users in small- to medium-sized cloud platform usage scenarios while reducing the complexity of system deployment and lowering the operation and maintenance costs of using the cloud platform.

The application discloses a kind of based on RPA BIM software automation test method and system.The method includes: through built-in embedded module, the interactive channel of two-way communication between RPA player and BIM software is established, the accurate driving of BIM software is realized;Create standardized test environment, system deployment includes input, output and document assets in basic test assets;Create the RPA automation test script of task-process-step hierarchical structure;Batch automation testing is carried out by forming OPR project file by organizing multiple scripts, and test report is generated.The corresponding system contains five modules of communication service, test asset management, test editing, test execution and test management.The application solves the problem of low BIM software test efficiency and strong artificial dependence, realizes the automation test and efficient regression verification of complex modeling process.

The application provides a kind of air conditioning start time prediction method and system suitable for cigarette factory manufacturing process, specifically includes system deployment and operation and maintenance, wherein the system deployment method includes, using the deployment scheme of background containerization, including the deployment of back-end service, the deployment of front-end interface and the deployment of front physical sensor, wherein the back-end service deployment includes deploying dedicated server.The advantage is that the data polling of appropriate time granularity is based on the feature engineering of multi-dimensional data to build a random forest to predict the air conditioning running time prediction, temporary adjustment strategy during prediction execution, and adaptive retraining of later model.The "trinity" air conditioning measurement and control effect of prediction intelligence, adaptive optimization of model and accurate measurement and control result is realized.

This invention discloses a 3D human motion digital twin method and system based on multi-camera hardware synchronization, belonging to the field of digital twin technology. It solves the technical problems of high cost of traditional optical motion capture, lack of depth information in monocular vision, and insufficient accuracy of 3D pose acquisition under limited viewpoints. The key points of its technical solution are that it only requires a small number of ordinary industrial cameras, combined with a low-cost TTL synchronization triggering scheme, to achieve reconstruction accuracy close to that of expensive optical motion capture systems, greatly reducing the system deployment threshold. Through virtual reprojection technology, it breaks through the limitations of physical site and number of cameras, and can simulate data from multiple virtual observation perspectives, effectively solving the pain points of single data perspective and poor generalization in traditional methods. The high-precision reconstructed 3D human skeleton data sequence obtained can be transmitted to the Unity 3D virtual engine environment to realize real-time motion driving and motion state reproduction of the digital twin virtual human model.

This invention belongs to the field of industrial internet and data security collaboration technology, specifically involving a CAD manufacturability assessment method based on federated agent decision-making. It includes global parameter initialization and local data preprocessing; structure-preserving interpolation pre-training; local joint optimization based on agent decision-making and feature classification; de-identification and isolation and cross-client federated global aggregation; global convergence determination and system deployment. This invention overcomes the technical shortcomings of existing industrial CAD assessment technologies, such as redundant computing power, incomplete historical data, and cross-enterprise data silos. While protecting the privacy of multiple parties' data, it effectively repairs incomplete historical CAD drawings and dynamically plans feature extraction paths.

This invention discloses a green renovation construction method for ancient buildings based on the concept of coexistence of old and new, including the following steps: construction and evaluation of a digital twin model of the building's full information; selective structural repair and reinforcement based on the principles of reversibility and minimal intervention; modular implantation and integration of adaptive functional systems; selection of regional ecological building materials and integration of old and new materials; deployment and operation and maintenance of an intelligent health monitoring and early warning system for the entire building life cycle. This invention, by disclosing a highly detailed and systematic construction method for the renovation of ancient buildings, innovatively proposes a complete set of technical processes and management logic that runs through the entire process of "evaluation-repair-renovation-operation and maintenance," and fully describes a comprehensive construction method centered on "repair, restoration, and reinforcement," integrating modern digital technology, green material technology, and intelligent monitoring technology, which has high promotional value.

This invention belongs to the field of LLM R&D and application technology, and discloses an automatic generation method for OPC UA information models based on LLM knowledge completion. First, it constructs a knowledge graph of OPC UA information models containing multiple heterogeneous industrial devices. Then, it constructs a dual-view inference LLM module, designing a context-adaptive inference example selector and a Bayesian disambiguation module to achieve semantic alignment and relationship prediction of unknown entities. Next, it constructs a knowledge completion LLM module based on structural prefixes, including a relation-guided multi-layer graph attention network and a projection layer, injecting the structural embedding of aligned nodes as prefixes into the LLM. Finally, it trains the knowledge completion LLM by fusing continuous vector prefixes and text vectors for joint fine-tuning, deploys the system in an industrial field, and generates standardized XML model description files. This invention can automatically construct OPC UA information models from structured equipment data, reducing manual intervention.

The application relates to a kind of factory equipment failure prediction method and system fusing causal inference, method includes: obtaining local time series data, and input trained local model, generate preliminary causal diagram;Initialize the parameters of global model;Based on preliminary causal diagram, by each client to local factory sensor time series data carries out causal perception data enhancement;Based on the local factory sensor time series data after data enhancement, comparative learning of local model is carried out, and the updated model parameter is uploaded to the server after encryption;By server running knowledge-guided aggregation algorithm, update the global model, and the updated global model is issued to each client;By each client, real-time acquisition local factory sensor time series data under different data sources, input global model, generate universality feature, and send into prediction model, generate fault analysis result.Compared with prior art, the application has the advantages of considering data security and flexible system deployment.

The application discloses a vision, inertia and active cursor based cooperative positioning method, device and medium, and relates to the technical field of cooperative positioning of virtual reality and augmented reality. The method comprises the following steps: estimating first attitude information of a first terminal device in a local coordinate system in real time; capturing active light-emitting identifiers of remaining terminal devices in a field of view, and identifying identities of observed terminal devices; calculating relative attitude information between the first terminal device and the observed terminal devices according to pixel positions of the captured active light-emitting identifiers in environment images; exchanging the first attitude information, the identities of the observed terminal devices and the corresponding relative attitude information; and constructing an optimization model of state variables of the first terminal device and the remaining terminal devices. The second attitude information of all terminal devices is obtained by solving the optimization model. The application realizes truly mobile multi-user cooperative positioning of wearing and using, and greatly improves the flexibility and scene adaptability of system deployment.

The present application relates to the technical field of agricultural intelligent equipment, and proposes a field weed intelligent identification method and device based on an improved YOLOv11 algorithm, which comprises the following steps: step one, field weed dataset construction and preprocessing; step two, constructing a data configuration file based on the preprocessed dataset, setting YOLOv11 model parameters, and constructing a basic YOLOv11 model; step three, constructing an improved YOLOv11 model; step four, training the improved YOLOv11 model; step five, evaluating the performance of the improved YOLOv11 model; and step six, system deployment and field identification implementation. By introducing an LDConv large-core deep convolution and bidirectional feature pyramid fusion network, and embedding a channel and spatial dual attention mechanism, the present application effectively enhances the model's representation ability for multi-scale weed features and discriminability in complex backgrounds, and improves the detection accuracy and robustness.

This invention discloses a profile governance system, method, and IO interconnect chip for the UB interconnect protocol. The profile governance system is deployed on the IO interconnect chip, which is positioned on the access path from third-party access objects to the UB interconnect domain. The profile governance system includes: a construction module, used to obtain static declarations of third-party access objects to construct capability descriptors and continuously collect operational information of third-party access objects to construct operational profiles; a binding module, connected to the construction module, used to obtain different governance templates based on static declarations and bind capability descriptors, operational profiles, and all governance templates in a binding list; and a governance module, connected to the binding module, used to detect consistency deviations between capability descriptors and operational profiles and perform governance using the corresponding governance templates. This invention improves the working efficiency of third-party access objects by binding capability descriptors and operational profiles and performing governance through governance templates.

An MMBI operating system deployment system includes a chassis housing a BMC device that includes a BMC memory subsystem and that is coupled to a host processing subsystem. The host processing subsystem provides a BIOS subsystem that, during initialization operations, instructs the BMC device to retrieve operating system installer information, and subsequently copies portions of the operating system installer information from the BMC memory subsystem to a host memory subsystem using an MMBI. The host processing subsystem then uses the operating system installer information in the host memory subsystem to provide an operating system installer subsystem that, during the initialization operations, instructs the BMC device to retrieve operating system image information, subsequently copies portions of the operating system image information from the BMC memory subsystem to the host memory subsystem using the MMBI, and installs an operating system using the operating system image information in the host memory subsystem.

This invention relates to the fields of edge computing, the Internet of Things (IoT), and electronic shelf label (ESC) management technology, specifically an ESC management system based on edge computing. Deployed in an edge gateway device, the system includes: an edge sensing module for collecting local environmental variable data, inventory status data, and the binding mapping relationship between goods and ESCs in the target area; a collaborative computing module for calculating the cross-strip collaborative pricing matching degree based on a lightweight rule engine and generating an initial collaborative pricing strategy; a boundary verification module for calculating the mandatory compliance rate of the business boundary according to business constraint rules and correcting the strategy; an instruction issuing module for issuing price update instructions to the corresponding ESCs; and an adaptive feedback module for generating latency adjustment rules based on edge strategies to reduce the computational complexity of the rule engine. This invention achieves rapid decision-making at the edge, cross-strip linkage, and secure price adjustment simultaneously.

The application provides a real-time window switching method and device based on shared memory and hardware monitoring instructions. The method comprises: configuring a local timer of a target processor into an end time trigger mode, and setting an entry of an interrupt vector as a bare interrupt processing entry bypassing a kernel standard interrupt entry and exit framework; during execution of the bare interrupt processing entry, independently maintaining per-processor dynamic tick accounting, and triggering an original timing interrupt path according to a preset interrupt period; a user state real-time thread sets hardware address monitoring on a cache line where a window state identifier is located, executes low-power consumption waiting with window end time constraints during a non-real-time window, after exiting the waiting due to shared memory page writing, confirms a window switching result in combination with a serial number and a window state identifier, and executes a corresponding real-time workload according to a real-time window start time stamp. The application can reduce window switching perception delay, improve real-time response certainty, and reduce system deployment and maintenance cost.