19 results about "Job stream" patented technology

The application relates to the technical field of artificial intelligence, and provides an interactive method, device, equipment, medium and program product of a customer service robot, the method comprising the following steps: determining a target operation process matched with a user demand indicated by a conversation context based on the conversation context; the conversation context is determined based on a user query to be replied and historical interaction data belonging to the same conversation as the user query; inputting process content corresponding to the conversation context and the target operation process into a node detection model to obtain a target process node to be executed output by the node detection model; the node detection model is used for determining a target process node most matched with the conversation context from a plurality of process nodes through semantic understanding capability; and generating reply information of the user query based on the target process node. The application solves the problem that a process execution is rigid and cannot adapt to user jump expression, realizes nonlinear and dynamic execution of an operation process, and further improves the interactive experience of the customer service robot.

The present application relates to the technical field of industrial data security management, in particular to a drilling site safety operation process digitization management method and system, comprising the following steps: collecting sampling time, rotating speed, drilling pressure, standpipe pressure and writing in alignment, comparing drilling pressure with interval and checking rotating speed and pressure range, extracting difference value and checking change threshold value, writing in parallel determination label and sorting, counting abnormality and checking threshold value to generate management account book. In the present application, through the alignment and sequential writing of sampling time, rotating speed, drilling pressure, standpipe pressure, ticket number, shift and well section, discrete parameters form continuous operation link and the abnormal time and attribution are clear, combined with drilling pressure interval, rotating speed range and pressure range synchronous checking, the multi-parameter parallel constraint relationship is constructed, the composite abnormal positioning is realized, the adjacent difference value and continuous window verification are superimposed, the mutation and cumulative deviation can be identified, the interval mismatch and continuous change are determined in parallel and recorded by time, and the identification accuracy and management consistency are improved.

The application relates to the technical field of data processing, and in particular to a batch processing file generation method and device, equipment, a storage medium and a program product. The method comprises the following steps: importing and displaying an import file, the import file is a file obtained after job flow information and job information are filled in a batch processing demand template; in response to an adjustment operation request received by an interface, the job flow information and the job information in the import file are adjusted; in response to a configuration operation request received by the interface, export information of the import file is configured; and a batch processing file is generated based on the adjusted job flow information, the job information and the configured export information. The method can improve processing efficiency.

This invention discloses a machine learning-based method and system for monitoring PIVAS (Portable Automated Vehicle Automation System) process behavior safety, relating to the field of image recognition technology. The method involves acquiring and preprocessing the monitoring video stream of the work area to obtain target video frames; inputting these target video frames into a detection model to detect key work objects during the operation, resulting in a first detection result including category and location information; determining the corresponding work status based on the first detection result; comprehensively analyzing the work status corresponding to multiple frames to determine basic work events; performing temporal correlation and integrity judgment on the basic work events according to work process rules to obtain a second detection result; and sending an anomaly alarm message to the review terminal when the second detection result is abnormal. This invention enables automated monitoring and anomaly identification of PIVAS dispatching operations, improving the efficiency of work safety monitoring.

This invention discloses a work process control method, terminal equipment, and storage medium. It utilizes a visual identifier (such as a safety helmet with directional features) that operators naturally wear upon entering the workshop, is stably identifiable from a vertical top-down view, and represents the axial orientation of the human body during work. This serves as a contactless, unobtrusive human-computer interaction intent sensor. By tracking the spatial position and orientation of this visual identifier, the system can silently perceive, understand, and verify manual operations without requiring any additional actions or clothing from the operator. This achieves seamless closed-loop control of the work process, representing a breakthrough in the interaction paradigm from "human reporting" to "environmental perception."

The application discloses a kind of based on Vue3 Seismic Operation Process Visualization and Parameter Dynamic Editing System, method and medium, belong to electric digital data processing technical field.The application includes: operation process control module, for parsing seismic operation XML file into JSON data and rendering flowchart based on AntvG6 drawing framework;Module parameter editing module, realize parameter automatic binding and real-time editing by the ref and reactive characteristics of Vue3;Function menu module, based on ES Module realizes component extension.The application combines front-end technology with seismic operation process editing, solves the technical problems of poor cross-platform compatibility, difficult expansion, serious interaction delay when data volume is large of traditional C / S architecture seismic software, realizes cross-device use in browser, instant feedback parameter editing, component function extension, interaction delay does not linearly increase with data volume, significantly improves the efficiency and flexibility of seismic operation design.The application is suitable for efficient operation process design in seismic exploration data processing field.

A unified identity authentication and authorization method and system for an industrial network environment, relating to the field of digital information transmission, is disclosed. In this method, user permissions are initially limited to read-only mode. When a user submits a job request, a standard operation flowchart is retrieved based on the work order. By comparing the current physical state of the equipment with the preconditions of the nodes in the flowchart, the system determines the currently executable operation nodes. Subsequently, the system combines and encrypts the instruction information to be executed, the status conditions, and the session identifier to generate a single-use valid authorization credential. When the industrial control gateway receives an instruction request, it verifies the validity of the authorization credential and the conformity of the equipment status, temporarily opens the instruction writing channel, and immediately closes the channel and cancels the credential after the instruction is issued. This application aims to reduce the risk of disruption to normal industrial production caused by unauthorized account use or unintentional misuse by internal personnel at unnecessary times.

This invention relates to the field of intelligent manufacturing and production management technology, specifically to an intelligent operation collaborative control method and system. The method includes: acquiring real-time video streams of the work area; calling a pre-trained neural network model to parse the video streams to identify fine-grained behavioral sequences of operators; comparing the identified behavioral sequences with pre-stored standard operating procedures to generate compliance judgment results; and generating and outputting corresponding guidance information to the work area when the judgment result indicates abnormal behavior. Furthermore, the method also includes analyzing behavioral data to generate on-site management optimization suggestions and quantitatively evaluating the effectiveness of the optimization measures. This invention achieves precise real-time monitoring and guidance of the operation process and enables on-site optimization and effect evaluation based on objective data, effectively improving the level of operation standardization, product quality consistency, and overall production efficiency.

This invention discloses a multi-machine collaborative method and system for multimodal cargo handling and transshipment, belonging to the field of logistics and transportation technology. By acquiring comprehensive information on transportation tasks and real-time status data of operating equipment, this invention clarifies cargo attributes, timeliness requirements, site constraints, and equipment operating parameters, avoiding deviations caused by data fragmentation during operations. This improves the targeting and feasibility of multi-machine collaborative operations, effectively reducing resource waste and operational delays caused by information gaps. Through a scientifically formulated plan, precise equipment scheduling, real-time process monitoring, and dynamic strategy adjustment workflow, combined with equipment selection, route planning, task allocation, and handover verification, it achieves orderly and efficient execution of multi-equipment collaboration. This ensures precise matching between equipment and tasks, synchronous coordination of the operational process, and rapid response to emergencies such as cargo damage and equipment malfunctions, improving handling and transshipment efficiency and cargo integrity, and enhancing operational resilience and flexibility.

This invention relates to the field of logistics management technology, and more particularly to an intelligent calculation and dynamic optimization method for logistics park operation processes, comprising: calculating the changes in the overall equipment status, task progress, and vehicle queuing density respectively, and merging the changes into an operation status index; for each pending task, reading the corresponding task completion ratio and task queuing density, calculating the node process pressure index and task priority index, until the calculation of all pending tasks is completed, and constructing a task priority queue; for each task in the task priority queue, calculating the matching score between the task and the equipment, generating a task execution allocation table, and simultaneously updating the load status of the equipment through an update function to generate equipment status update values; reading the task execution allocation table, calculating the task adjustment index, re-evaluating the matching between tasks and equipment, and generating an optimized task execution allocation table and equipment status update values.

The application relates to a system for realizing unified job automation management and execution in a multi-cloud environment, comprising a script management module for centrally managing, version controlling, classifying and label managing and online testing of multiple script languages; a template management module for defining standardized job process templates, supporting global variables, inter-step data transmission and execution strategy configuration; a scheme management module for providing execution strategy configuration; and an execution record module for recording detailed processes of each execution and performing multidimensional query and visual display. The system for realizing unified job automation management and execution in a multi-cloud environment adopts the application, establishes a complete execution tracing system, records detailed states of the whole life cycle of jobs, supports quick positioning and optimization of problems, designs a dynamic resource scheduling mechanism, automatically adjusts execution resources according to loads, improves resource utilization efficiency, constructs an open and extensible system architecture, and supports unified job management in a multi-cloud and mixed environment.

This invention discloses a digital adaptive control method and system for power operation processes, relating to the field of power operation management technology. The method includes: acquiring relevant power operation data and constructing a basic operation dataset; constructing a power operation task model based on the data, parsing the operation plan to generate target operation tasks and characteristic parameters; using the characteristic parameters to conduct risk assessment and determine the operation risk level; generating a collaborative operation process based on the risk level; scheduling and controlling the execution of target operation tasks and acquiring execution status data; monitoring operation tasks based on execution status and adjusting the collaborative operation process when anomalies are detected. This invention enables digital, dynamic, and adaptive control of power operation processes.

This invention belongs to the field of perovskite optoelectronic materials technology, specifically an automated high-throughput perovskite thin film preparation system. The system includes: a glass substrate gripping device, a solution addition and removal unit, an automatic spin-coating unit, a vacuum flash evaporation unit, and an annealing device. The modules are connected via a communication bus or local area network to achieve bidirectional data and command interaction. The system collects parameters in real time through a unified data bus and stores them in a database, achieving full process traceability. All components are controlled digitally via the I / O interface of a robotic arm, and the program is written through the robotic arm's teach pendant. This invention supports collaborative optimization and iterative processing of workflows using machine learning and generative AI, achieving closed-loop control without human intervention. It utilizes a robotic arm and redundant units to verify multi-dimensional experimental procedures while ensuring emergency response capabilities and experimental breakpoint preservation. It also enables efficient task execution sequence design.

This application provides a job scheduling method, apparatus, electronic device, storage medium, and computer program product. The method includes: constructing a first directed acyclic graph (DAG) based on a first job flow, wherein the data input, task execution process, and data output of each computing task in the first job flow are represented by a first node in the first DAG, and the edge between every two first nodes in the first DAG represents the corresponding data flow direction; merging one or more first nodes in the same community of the first DAG into a second node based on a community detection algorithm to obtain a second DAG, wherein the edge between every two second nodes in the second DAG is used to indicate the dependency relationship between different communities of the first DAG; and scheduling one or more computing tasks corresponding to the same second node in the first job flow to the same computing cluster based on the second DAG.

The application discloses a standard operation procedure (SOP) behavior process detection method and system, and particularly relates to the field of detection and analysis, and comprises the following steps: S1, continuously collecting a work area video stream, calibrating core collection parameters, and completing total frame number formula calculation and region of interest coordinate calibration; S2, video stream decoding and frame extraction, completing full-process frame preprocessing, executing brightness normalization formula calculation and resolution unification; S3, preprocessed image frame-by-frame analysis, completing multi-dimensional target identification screening, calibrating target bounding box and confidence, and generating continuous space-time trajectory; the application builds a SOP behavior process full-link detection technology closed loop based on a video stream, upgrades the paradigm of industrial visual detection from product static result post-checking to in-process control of personnel operation behavior process, fills the gap of the prior art in SOP execution process monitoring, and can identify operation sequence errors, step omissions, illegal operations and other process abnormalities in real time.

This invention provides a method and system for constructing a hydropower station simulation training system based on multi-source collaboration, belonging to the field of hydropower station training technology. First, it integrates core multi-source training resources of hydropower stations to form a multi-source training core resource pool, covering core resources for equipment operation, work processes, and scenario responses. Next, it constructs a dynamic collaborative architecture for each resource within the multi-source training core resource pool and builds multi-directional interactive links based on this dynamic collaborative architecture to achieve real-time data interaction and scenario and behavior linkage. Based on the dynamic collaborative architecture and multi-directional interactive links, it generates an adaptive simulation training scenario that integrates the collaborative content of the multi-source training core resources. Finally, it collects feedback optimization data and iteratively adjusts the architecture parameters and link rules to form a closed loop. This invention improves the comprehensiveness, collaboration, and personalization of hydropower station training.

This invention relates to a method, system, medium, and equipment for automatic classification and multi-dimensional querying of spare parts procurement, including: constructing a big data platform based on multi-source data; dividing spare parts procurement progress nodes according to the spare parts procurement workflow and sub-workflows; acquiring procurement application and line number data of the target type from the big data platform, and classifying the procurement applications according to the spare parts procurement progress nodes and procurement progress classification strategies to obtain procurement application classification data; statistically analyzing the procurement application classification data and classifying it to the corresponding spare parts procurement progress nodes, and displaying the data records on the corresponding spare parts procurement progress nodes in the visualization process; simultaneously constructing a multi-dimensional fast query path and generating a list of key nodes. This invention automatically captures multi-source data, automatically classifies spare parts procurement progress, and visualizes it, automatically summarizing the lists of each node, automatically providing classification lists for manual intervention, significantly improving procurement efficiency and contract performance.

Systems and methods are provided to track and calculate the carbon generated by individual processing stages of a processing pipeline or an individual artifact. The system may track and store the lineage / dependencies of the data from individual applications that are involved in the processing pipeline. The applications may transmit their metadata to the system to record the metadata associated with the execution. The system can track the carbon footprint from start to finish of individual stages at the job / pipeline level or each of the processing steps of generating the individual artifact.

This invention discloses a material scheduling method, apparatus, equipment, medium, and product. The method includes: acquiring delivery equipment data, delivery task information destined for a target machine, and material operation data of the target machine at the current time; determining the latest call time for the target machine to initiate a material request based on the current time, delivery equipment data, delivery task information, and material operation data; when the current time is earlier than the latest call time, determining the delivery load attribute based on the task flow data destined for the target machine within a preset time window; and determining the target material request method based on the delivery load attribute, the latest call time, the current time, and the material operation data, and initiating a material request based on the target material request method. The technical solution provided by this invention improves the timeliness and reliability of material delivery, reduces the risk of machine downtime due to material shortages and material blockage at the production line, thereby ensuring the safety and smooth operation of the production site.