25 results about "IT service management" patented technology

A predictive incident management system, consisting of: a sensor input module configured to receive heterogeneous telemetry data streams from mechanical, thermal, electrical and cyber sources; a temporal correlation control unit operationally coupled to the sensor input module, wherein the temporal correlation control unit is configured to normalize received data into a uniform time series envelope that includes identifiers, microsecond-precision timestamps, metric names, values, and context markers, and is further configured to compute sliding window-cross-sensor correlation matrices, event motifs, and lead-lag dependencies across multiple time granularities; a scalable rule processor that is communicatively linked to the control unit for temporal correlation, wherein the rule engine includes an in-memory runtime environment for processing complex events and a domain-specific declarative language, and is configured to apply rules that reference primitive sensor metrics, derived correlation features, and motive-based early warning vectors to classify, escalate, or resolve predicted incidents; A historical repository that is communicatively connected to both the temporal correlation control unit and the rule engine. The repository is configured to store tagged event histories, correlation motif dictionaries, rule versions, and rule origin metadata to ensure the verifiability and explainability of predictions; and An incident response interface is operationally connected to the rule engine. The incident response interface is configured to trigger automated workflows, including the generation of tickets for IT service management, chat ops notifications, the execution of orchestration playbooks, and direct machine control via industrial protocols. the system is configured to perform predictive analyses based on temporal correlations between sensors and to execute context-aware, rule-based incident management in real time.

The invention relates to the field of information technology service management, and discloses an automatic work order processing method and system based on a process orchestration engine, and the method comprises the following steps: S1, carrying out semantic analysis, and obtaining feature information; s2, constructing a processing flow based on the feature information; s3, performing resource scheduling and automatic execution on the processing flow; s4, carrying out case recording; and S5, performing iterative optimization on at least one of the first preset model, the second preset model and the third preset model. The system comprises a work order analysis module, a process arrangement engine, a process execution module, a case recording module and a model optimization module. According to the method, work order semantic analysis is performed through the pre-training language model, and atomic operation utility is dynamically evaluated in combination with the Bayesian network model, so that the service intention can be automatically identified, the key entity can be extracted, and the optimal execution path can be reasoned and selected.

A system for the automated collection of test results and conformity reporting in IT service management environments. The system includes: a structural enclosure configured to enclose a variety of electronic components, wherein the structural enclosure is equipped with power supply circuits, thermal control units and electromagnetic shielding; at least one processor located within the structural housing and electrically connected to a communication controller, wherein the processor is configured to execute instructions for interface with distributed data sources for information technology service management; The communications controller includes a variety of encrypted data transmission circuits configured to securely extract evidentiary data from service management logs, access control records, configuration baselines, and monitoring databases; a compliance controller electrically connected to the processor, wherein the compliance controller comprises a rule-based processing unit configured to identify evidence artifacts required by a compliance framework, and a verification processing unit configured to validate the integrity, completeness, and format of the extracted artifacts; a time synchronization circuit electrically coupled to the compliance controller, wherein the time synchronization circuit is configured to assign tamper-proof cryptographic timestamps to each evidence artifact at the capture location; a memory management circuit electrically connected to the non-volatile memory, wherein the memory management circuit is configured to organize the validated evidence artifacts in a hierarchical and indexed data structure, with indexing being performed according to service identifiers and conformance categories; a hardware security controller located within the structural enclosure, wherein the hardware security controller includes a secure enclave configured to store cryptographic keys and to digitally sign evidence artifacts and compliance reports prior to their transmission; and an output interface that is electrically connected to the compliance controller and the hardware security controller, wherein the output interface is configured to generate compliance reports in both machine-readable structured formats and human-readable formatted documents and to transmit these reports to authorized audit systems.

This invention discloses a task scheduling method and system based on an ITSM platform, belonging to the field of IT service management technology. The method includes the following steps: acquiring an available execution node cluster; collecting task execution records of nodes within a second scheduling set to generate a true performance baseline; performing periodic node rotation operations between the first and second scheduling sets based on historical execution data and the true performance baseline; calibrating the historical execution data of the first scheduling set; monitoring the real-time load distribution of the first scheduling set to trigger emergency node rotation operations; performing emergency node rotation operations and resetting historical data for nodes that have undergone rotation; and updating the initial node quantity ratio. This invention solves the problems of hotspot solidification, self-fulfilling oracle, and cluster resource utilization imbalance caused by historical affinity bias in existing technologies by dividing execution nodes into a first scheduling set and a second scheduling set.

Information technology service management (ITSM) is provided by at least one computing device, including by accessing plurality of ITSM requests. For each one, a determination is made whether the respective ITSM request is valid. Where the request is not valid, a status identifier is assigned. Where the request is valid, the computing device(s) identifies, in the respective ITSM request, request information representing at least a request for action associated with a back-end service, a target service name, and a target system. Further, the computing device(s) distinguishes in the respective ITSM request, as a function of at least the request information, a technical infrastructure detail associated with the back-end service. Moreover, the computing device(s) generates, as a function of the technical infrastructure detail, a notification for implementing the action and transmits to at least one computing device associated with the back-end service the notification for implementing the action.

A plurality of correlations is determined including by applying a machine learning model to a first plurality of features extracted from a plurality of information technology and operations management alerts and information technology service management reporting data. Each correlation of the plurality of correlations is between a corresponding one of the plurality of information technology and operations management alerts and at least one corresponding portion of the information technology service management reporting data. The information technology service management reporting data includes at least one urgency indicator. A prioritized list of information technology and operations management alerts is generated based at least in part on the determined plurality of correlations and the at least one urgency indicator. The prioritized list of information technology and operations management alerts is organized based at least in part on relative priorities of the alerts.

The invention discloses an IT service work order intelligent classification and priority dynamic adjustment method and system, and belongs to the technical field of work order classification adjustment, and the method specifically comprises the steps: obtaining to-be-processed IT service work order data, carrying out the mapping to generate a work order feature image, carrying out the analysis of an IT service work order through a preset feature recognition model, and carrying out the priority dynamic adjustment of the IT service work order. Determining a work order category corresponding to the IT service work order, constructing a work order priority visual energy field model, generating a dynamic priority score corresponding to the real-time state of the IT service work order, and updating the work order feature image and the work order priority visual energy field model according to the state change of the IT service work order in the IT service work order processing process. According to the IT service work order processing method and device, comprehensive expression and consistent processing of complex work order features are achieved, dependence on artificial experience and static rules is reduced, and the IT service management requirements of high concurrency and multiple scenes are met.

This invention relates to the field of information technology service management, and discloses an automated work order processing method and system based on a process orchestration engine. The method includes the following steps: S1, performing semantic parsing and obtaining feature information; S2, constructing a processing flow based on the feature information; S3, scheduling resources and automating the execution of the processing flow; S4, recording cases; S5, iteratively optimizing at least one of the first, second, and third preset models. The system includes a work order parsing module, a process orchestration engine, a process execution module, a case recording module, and a model optimization module. This invention uses a pre-trained language model for work order semantic parsing and combines a Bayesian network model to dynamically evaluate the utility of atomic operations, thereby automatically identifying business intent, extracting key entities, and inferring and selecting the optimal execution path.

The invention belongs to the technical field of digital finance, and particularly discloses a data quality checking system, which is used for checking the quality of data in a to-be-checked system, and comprises a quality rule configuration and management module used for maintaining a checking rule which is used for evaluating the quality of the data; the quality rule running and monitoring module is used for pushing a current checking rule to the to-be-checked system, receiving a checking result fed back by the to-be-checked system and monitoring the execution condition of the to-be-checked system; and the data quality problem management module is used for generating check problems according to check rules which do not pass execution, analyzing and processing the check problems, and connecting an external IT service management platform problem list management process. The method has the advantages that normalized check and management of transaction data are realized by periodically executing and operating check rules of the data quality check system, and a mode of passively waiting for supervision to discover data quality problems is changed into a mode of actively discovering and solving the problems from the source.

The invention discloses a hospital information department operation and maintenance management system based on artificial intelligence, which relates to the technical field of information technology service management and comprises a data analysis module, an event merging module, a repetition identification module, a constraint arrangement module and a rhythm regulation and control module. Real-time monitoring signals, work order records, personnel scheduling information and equipment operation state information in the operation and maintenance management stage are collected, collected data are analyzed in a centralized mode, an operation change diagram is drawn according to the fluctuation amplitude of the monitoring signals, and an interference time period is extracted to serve as a time reference. According to the method, through multi-source signal analysis and event merging of the time reference, homologous anomaly accurate identification is realized, repeated work orders are reduced, and the operation and maintenance response efficiency is improved; through triggering threshold and delay control and cooling period adjustment, event triggering order and stable signal feedback are realized, and intelligent scheduling and efficient operation of hospital information operation and maintenance are guaranteed.

Methods, apparatuses, and computer program products are disclosed for updating and outputting an information technology service management user interface comprising a queue interface component pane. In an example embodiment, an apparatus accesses a user identifier and a team identifier associated with the information technology service management user interface, identifies a plurality of queue identifiers associated with the user identifier and the team identifier, initiates retrieval of queue issue count data for the plurality of queue identifiers from an issues data repository during an aggregated queue latency period, generates an updated queue interface component based on the queue issue count data for a selected queue identifier in a circumstance where queue issue count data is retrieved prior to the expiration of the aggregated queue latency period, and outputs the updated queue interface component to the information technology service management user interface for rendering to the queue interface component pane.

Information technology service management (ITSM) incident reports are converted from textual data to multiple vectors using an encoder and parameters are selected, where the parameters include a base cluster number and a threshold value. A base group of clusters is generated using an unsupervised machine learning clustering algorithm with the vectors and the parameters as input. A cluster quality score is computed for each of the base group of clusters. Each cluster from the base group of clusters with the cluster quality score above the threshold value is recursively split into new clusters until the cluster quality score for each cluster in the new clusters is below the threshold value. A final group of clusters is output, where each cluster from the final group of clusters represents ITSM incident reports related to a same problem.

A computer-implemented method for handling inbound service requests analyzes content of the message to extract a set of features, and generating a feature vector based on the set of extracted features. A categorization metric for the feature vector is then determined, using a set of predetermined categorization vectors, wherein each predetermined categorization vector corresponds to a respective portal endpoint associated with one or more predefined ticket types and sub-types of an information technology service management system. In response to the categorization metric satisfying a comparison criteria with respect to one or more predetermined categorization vectors, a particular portal endpoint is selected. Content from the email message is then extracted. A new issue object request is then automatically generated in accordance with a particular object requirement set associated with the particular portal endpoint for submission to an issue tracking system to create a new issue object.

The invention relates to the technical field of information technology service management, in particular to an information technology service system based on technology service data analysis. The system comprises an input processing module for receiving user input through a user interface and preprocessing the user input; the initial answer generation module is used for generating an initial answer for user input by utilizing a pre-constructed knowledge base; the answer rechecking module is used for selecting an AI expert which is most matched with the initial answer field to check and improve the initial answer; the output module is used for converting the answers checked and perfected by the AI experts into interactive and visual visual formats and outputting the answers to a final user; and the feedback collection module receives evaluation information of the user on the output result and is used for system optimization. According to the method, the AI expert cooperative workflow is constructed, so that rapid and accurate response to the information technology service request is realized, the solving efficiency and the service quality of complex technical problems are improved, and the method has a continuous self-optimization capability.

A method for dynamic scaling of IT services management includes receiving a selection of IT services, initializing machine avatars based on demand, dynamically adjusting these avatars, establishing network tunnels, and managing network traffic to optimize resource utilization. A system for this includes a processor and memory to perform these operations. A computer-readable medium stores instructions for these operations to optimize IT service responsiveness.

This invention discloses an information technology management consulting system and method for intelligent information technology service management, relating to the field of fault information maintenance technology. Addressing the problems of existing operation and maintenance knowledge bases relying on manual updates and having low retrieval matching accuracy, this invention's method first intercepts and cleans operation and maintenance terminal operations to generate standardized event sequences; then, it generates knowledge records by aligning asset topology attributes with monitoring alarm context; when new fault features match topology attributes, it recommends knowledge and captures feedback; further, it establishes a credibility scoring model based on the state transition of fault work orders to dynamically verify and score knowledge; finally, it achieves automated admission and removal management of the knowledge pool based on credibility scores. This invention also discloses a corresponding management consulting system. This invention realizes the automated accumulation and closed-loop iteration of operation and maintenance knowledge, establishes a strong logical association between operations and fault root causes, and significantly improves the accuracy and executability of knowledge recommendation.

The embodiment of the invention belongs to the technical field of artificial intelligence, and relates to an event priority evaluation method and related equipment applied to IT service management, and the method comprises the following steps: carrying out word vector conversion operation on an event description text according to a word vectorization method; performing classification model training operation on the initial support vector machine classification model according to the event classification label; inputting the event feature vector into a target support vector machine classification model for classification operation; performing prediction model training operation on the initial random forest regression model according to an event grading result; inputting the event feature vector and the event classification result into a target random forest regression model for prediction operation; constructing an event priority judgment rule according to the business rule and the technical index; and determining a priority evaluation result of the historical event data according to the event classification result, the severity score and an event priority judgment rule. The operation and maintenance efficiency can be greatly improved, and the workload of operation and maintenance personnel is reduced.

The application provides an IT service management method, device and server. The method comprises the following steps: obtaining a service request order submitted by a user for an IT service management system; determining a current service priority of the service request order according to a service item; distributing the service request order and the current service priority to a terminal of a worker at a corresponding level according to a service area and the service item, so that the terminal of the worker updates a corresponding task list; if it is monitored that the current worker cannot solve the service request order, sending the service request order and the corresponding service priority to a terminal of a worker at a next level based on a service range and the service item, so that the terminal of the worker at the next level updates a corresponding task list. Through the above method, the application can improve the completion efficiency of the service request order and avoid the problem that single combat causes the service request order to be delayed and cannot be solved, and the management is complicated.

A system (100) for automated configuration mapping and relationship derivation to improve the accuracy of the configuration management database (CMDB), consisting of: a data acquisition module configured to continuously collect configuration data from heterogeneous IT infrastructure sources, including cloud platforms, local systems, network devices, and virtual environments; a normalization and matching module configured to standardize the collected data, eliminate duplicates, and match the data against a predefined CMDB schema; a configuration mapping engine configured to identify and classify configuration items (Cls) based on metadata, identifiers, and behavioral patterns; a module for deriving relationships that is configured to automatically detect and derive dependencies between Cls using machine learning algorithms and pattern recognition techniques; a validation and conflict resolution module configured to check the consistency of the derived relationships and correct any data inconsistencies; a visualization and reporting module configured to provide real-time graphical representations of CI relationships and infrastructure changes; and an integration and update module configured to synchronize validated configurations and relationships with the CMDB and associated IT Service Management (ITSM) tools.

Information technology service management (ITSM) is provided by at least one computing device, including by accessing plurality of ITSM requests. For each one, a determination is made whether the respective ITSM request is valid. Where the request is not valid, a status identifier is assigned. Where the request is valid, the computing device(s) identifies, in the respective ITSM request, request information representing at least a request for action associated with a back-end service, a target service name, and a target system. Further, the computing device(s) distinguishes in the respective ITSM request, as a function of at least the request information, a technical infrastructure detail associated with the back-end service. Moreover, the computing device(s) generates, as a function of the technical infrastructure detail, a notification for implementing the action and transmits to at least one computing device associated with the back-end service the notification for implementing the action.

This invention discloses an artificial intelligence-based hospital information department operation and maintenance management system, belonging to the field of information technology service management technology. It includes a data analysis module, an event merging module, a duplicate identification module, a constraint orchestration module, and a rhythm control module. The data analysis module collects real-time monitoring signals, work order records, personnel scheduling information, and equipment operating status information during the operation and maintenance management phase. It performs centralized analysis on the collected data, draws an operation change graph according to the fluctuation amplitude of the monitoring signals, and extracts interference periods as a time base. This invention achieves accurate identification of common-source anomalies through multi-source signal analysis and event merging using a time base, reducing duplicate work orders and improving operation and maintenance response efficiency. Through trigger threshold and delay control and cooldown period adjustment, it achieves orderly event triggering and stable signal feedback, ensuring intelligent scheduling and efficient operation of hospital information maintenance.

The invention relates to the technical field of knowledge graphs, in particular to an IT service management system based on a knowledge graph, which comprises a fault information extraction module, a historical experience pruning module, a semantic association expansion module, a semantic similarity expansion module, a data processing module, a data processing module, a data processing module, a data processing module and a data processing module, and is characterized in that the fault information extraction module acquires a work order traversal graph to generate an initial range, and the historical experience pruning module retrieves historical work order intersection operation to obtain a pruned set; and the influence domain aggregation module combines the two sets to generate and display a refining fault influence range. According to the invention, the knowledge graph is constructed to carry out topological traversal to obtain the initial influence range, and the actual operation record set analyzed in the historical work order is utilized to carry out intersection operation on the initial influence range, so that accurate pruning of theoretical association configuration items is realized, interference of irrelevant configuration items is remarkably reduced, and the accuracy of the pruning of the theoretical association configuration items is improved. By calculating the cosine similarity between a current fault description text vector and a candidate configuration item attribute text vector, hidden affected configuration items which are lack of topological paths but highly similar in function are expanded and recognized, and a refined influence range is formed through aggregation.

A computing system includes a processor, a network interface controller (NIC) configured to communicate via multiple networks; a virtual desktop infrastructure application (VDIA) including computer-executable instructions configured to: perform operations and maintain a virtual hosting environment; remediate a finding by hardening network access; and notify a user of a potential issue before an incident occurs; and an information technology service management application (ITSMA) interoperable with the VDIA. A computer-implemented method includes configuring a NIC to communicate via multiple networks; accessing an ITSMA; performing operations to maintain a hosting environment; remediating a finding by hardening network access; and notifying a user of an issue. A non-transitory computer readable medium includes computer-executable instructions that when executed, cause a computer to: configure a NIC to communicate via multiple networks; access an ITSMA; perform operations to maintain a hosting environment; remediate a finding by hardening network access; and notify a user of an issue.

This invention relates to the field of information technology service management technology, and discloses a method, system, and storage medium for processing the allocation of maintenance personnel. The method includes: acquiring work order fulfillment data, workload data, on-call duty requirement data, and automation coverage data of the target maintenance object within a preset statistical period; determining the basic configuration number based on the workload data, and generating a risk adjustment factor based on the work order fulfillment data; determining the additional on-call duty requirement based on the on-call duty requirement data, and determining the automation reduction number based on the automation coverage data, and generating a preliminary staffing number; constraining and calibrating the preliminary staffing number to obtain the target staffing number; and dynamically adjusting the target staffing number based on the correspondence between the risk adjustment factor and a preset risk threshold range, combined with the judgment results of the continuous statistical period. This application improves the accuracy, stability, and executability of the maintenance personnel allocation results.