90 results about "Project manager" patented technology

An AI-powered agile project management system for automatic risk assessment and mitigation, including: a risk identification module configured to extract project data from agile project management tools, including but not limited to Jira, Trello, Asana, and Monday.com, and identify potential risks using machine learning and NLP; a risk analysis module configured to assign risk scores based on probability, impact, and severity using predictive analytics, where the module uses historical data, real-time project status, and external dependencies to determine the severity and impact of risks; a real-time monitoring module configured to continuously track project conditions, detect anomalies, and generate immediate notifications via email, mobile apps, or messaging platforms when high-risk events are identified; a risk mitigation module configured to dynamically recommend and execute proactive corrective actions such as task reassignment, resource optimization, schedule adjustments, and implementation of alternative strategies using AI-driven decision-making, where the actions can be automated through predefined workflows or manually adjusted based on AI recommendations; an AI-driven task prioritization module configured to dynamically prioritize tasks based on risk factors, project deadlines, and team workload distribution; an integration module configured to ensure seamless compatibility with existing Agile project management frameworks through API-based synchronization; a learning and continuous improvement module configured to refine risk prediction models over time using machine learning and historical risk mitigation results, with AI-driven models continuously updating risk assessment mechanisms based on evolving project conditions, industry-specific risk factors, and historical performance metrics; a compliance and audit reporting module configured to automatically generate risk reports, audit logs, and compliance checklists; a customizable risk assessment configuration module configured to allow project managers to define custom risk parameters, probability thresholds, and mitigation preferences; an interactive dashboard module configured to visualize data in real time, including risk trends, effectiveness of remedial actions, and analysis of project progress; and a scalability feature configured to be used in industries such as IT, healthcare, finance, construction, and manufacturing.

The invention relates to the technical field of project management and artificial intelligence, in particular to a project progress tracking and risk prediction system and method based on an improved knowledge graph and a multi-view graph neural network, and the system comprises a knowledge graph construction and dynamic updating module, an improved graph neural network analysis module, and an anomaly detection and risk prediction module. An intelligent early warning and visualization module; the method has the beneficial effects that anomaly detection is carried out through the GAN, possible delay and risk of a project are predicted, a risk early warning report is automatically generated, and optimization suggestions are provided for project managers. The system has the advantages of dynamically updating the knowledge graph in real time, improving risk prediction accuracy and enhancing project management perspectiveness and intelligent decision support, and is suitable for progress tracking and risk control in complex project management.

The invention provides an intelligent project management system based on supervision integration, and the system employs a cloud platform for deployment, and comprises a project management module which is used for task management, progress tracking and document sharing, so as to achieve the planning, starting, execution, monitoring and ending of a whole life cycle of a project; the data acquisition and integration module is used for collecting project data in real time and performing integration processing; the risk assessment and early warning module is used for performing risk assessment on the project data and giving out early warning when the risk exceeds a preset threshold value; the intelligent decision support module is used for providing decision suggestions for a project manager based on the data analysis result; and the visual display module is used for visually displaying information such as a project state, progress, cost and quality in forms such as charts and reports. According to the system, through an integrated management platform and an intelligent analysis tool, real-time monitoring, risk assessment, resource optimization and decision support of the full life cycle of a project are realized, so that the project management efficiency is improved, and the project risk is reduced.

The invention discloses a project cost risk monitoring method and a project cost management platform, and the method comprises the steps: S1, carrying out the real-time collection and standardization processing of multi-source data: collecting dynamic data in real time through an Internet of Things device at a construction site, carrying out the butt joint of a design drawing, a financial system and the like, obtaining static data, and employing a data cleaning, conversion and integration technology; s2, carrying out risk factor identification and correlation analysis based on a knowledge graph; s3, implementing risk quantitative prediction and early warning driven by artificial intelligence; s4, real-time monitoring and automatic verification of contract performance of blockchain enabling are realized; s5, providing dynamic cost adjustment and optimization decision support; through real-time collection and standardization processing of multi-source data, data islands of all parties participating in a project are broken, and accuracy, integrity and timeliness of key data such as construction progress and cost expenditure are ensured. Based on big data analysis and artificial intelligence prediction, more accurate risk assessment and cost prediction are provided for project managers.

The invention discloses a construction engineering management quality control system and a risk management method, and relates to the technical field of construction engineering management, and the key point of the scheme is that the system comprises a risk analysis module, an engineering environment monitoring module, an engineering quality detection module and a structure specification examination module. According to the method, dynamic management of project quality and risks is realized by analyzing construction project data and monitoring a project site in real time, the risk level of the construction project is accurately quantified through multi-factor risk assessment, and compared with a traditional method, potential risks can be identified in the early stage of the project, prevention measures can be taken, and the risk level of the construction project can be accurately evaluated. The potential risk occurrence rate is remarkably reduced, the transparency of the construction process is improved through integrated analysis of real-time videos and sensor data, project managers can monitor quality control points in real time, construction strategies are adjusted in time through immediate recognition and analysis of concrete surface defects, the construction process is optimized, and the construction efficiency is improved. And the overall safety and success rate of project management are improved.

The invention discloses an electric power engineering project management talent intelligent evaluation and dynamic training system, and the system comprises a multi-dimensional quality capability model construction module which constructs a four-dimensional capability framework based on the characteristics of an electric power engineering industry, generates a differentiated post capability model through a dynamic weight distribution algorithm, and carries out the dynamic training of the differentiated post capability model; constructing an industry ability dictionary library by utilizing a knowledge graph technology; the intelligent evaluation and matching module integrates a multi-modal evaluation tool to collect dominant and implicit capability data, dynamically adjusts capability index weights through a pre-trained AI model based on project characteristic parameters, and calculates man-post adaptation indexes by adopting a cosine similarity algorithm; and the dynamic training and development module is used for generating a personalized training scheme by quantifying the capability difference, tracking the training effect in a closed-loop manner based on a Korotkoff four-level evaluation model, and dynamically optimizing a training path by adopting a Bayesian network. The technical defects of single evaluation dimension, low man-post matching degree and insufficient cultivation efficiency of traditional power engineering human resource management can be solved.

The invention relates to a progress monitoring method based on digital twinning and a BIM (Building Information Modeling) information management system, which can realize automation of a progress monitoring process and can provide more accurate and more objective building activity progress information. By using a three-dimensional information front view and a deep learning-based semantic segmentation technique, the completion percentage of the construction activity can be detected and reported. According to the invention, construction management personnel can be helped to track the progress of main structures such as beams, columns, floor plates and the like, and potential delay or problems can be found as early as possible in the construction process. Through BIM color coding and a point cloud segmentation technology, the progress of each activity can be visualized, so that a project manager is helped to make a more intelligent decision, and resource allocation is optimized.

The invention belongs to the technical field of shipping big data application, and particularly relates to a shipping research report generation method based on multi-agent cooperation, and the method comprises the steps: enabling a multi-agent hierarchical cooperation architecture, dividing a whole agent into a plurality of sub-agents with independent functions, and dividing the sub-agents into a management layer and an execution layer; the management layer comprises a project manager agent, an architect agent and a demand side agent; the execution layer comprises a shipping intention recognition agent, a background investigation agent, a content team agent, a review verification agent and a report writing agent; the intelligent agents cooperate with one another, and a shipping research report is written in a popular, easy-to-understand, organized and clear language according to the structure and style of the shipping report. According to the method provided by the invention, human information processing, decision making and operation processes are simulated, a modularized and multi-agent cooperative agent scheme is constructed, and the application of AI in the shipping field is pushed to a new height of comprehensive knowledge creation from operation assistance and single analysis.

The invention discloses a large-scale offshore wind power networking sending scheme evaluation method. The method comprises the following steps: constructing a multi-dimensional comprehensive evaluation system of a large-scale offshore wind power sending system, constructing a multi-dimensional comprehensive rating model of large-scale offshore wind power networking sending, determining an improved scale analytic hierarchy process and a principal component dimensionality reduction method to perform subjective and objective weighting on indexes, and determining game theory Nash equilibrium comprehensive weighting. And determining a good and inferior solution distance method to comprehensively evaluate each technical scheme. The method is beneficial for a project manager to master the actual operation and operation conditions of the wind power plant sending-out system, summarizes the advantages and disadvantages, and provides a set of complete and effective evaluation system and evaluation method for the management decision of a future project.

The invention discloses an RAG-based project management experience processing method and a storage medium, and the method combines two functions of retrieval and generation of an RAG technology, firstly retrieves related information, then generates a high-quality natural language text, and finally integrates the high-quality natural language text into a question and answer system, and the project management experience processing efficiency is improved through an intelligent chat mode. An accurate technical scheme can be quickly provided for a project manager, and the project manager is helped to efficiently identify and solve potential problems in a project, so that the decision quality and execution efficiency of project management are remarkably improved.

A system (100) for adaptive real-time planning in construction projects using location and production feedback, wherein the system comprises: a data acquisition module configured to capture real-time data from construction site sensors, IoT-enabled devices, construction machinery, workforce systems, and material supply updates; a central processing engine configured to analyze deviations between planned schedules and actual site performance using adaptive planning algorithms; an intelligent feedback loop that integrates qualitative input from site managers, engineers and project managers to refine planning decisions; a visualization and dashboard module configured to display updated schedules, resource allocations, predictive alerts, and progress indicators in real time; and an integration and communication module configured to synchronize adaptive schedules with existing construction project management platforms, The system continuously updates and optimizes the schedules of construction projects to improve efficiency, resource utilization, and on-time completion.

The invention relates to the technical field of engineering supervision platform information transmission, and discloses an information transmission method and system based on an engineering supervision platform, and the method comprises the steps: obtaining construction data uploaded by an on-site supervisor, executing a classification compression preprocessing strategy, and carrying out the classification compression and robust coding of the construction data; executing a double-layer encryption strategy according to the execution key and the construction data, generating a digital signature, and encrypting the construction data, the execution key and the digital signature; sending the encrypted construction data, the execution key and the digital signature to a project manager through a network transmission path; executing a fault monitoring strategy on each node in the network transmission path, and judging whether the node has a fault or not; if the faulty node is monitored, executing a multi-level redundant backup strategy, and replacing the faulty node with the backup node; a hierarchical processing strategy is performed on the abnormal network behavior, the security of a network transmission path is maintained, and the efficiency and security of data transmission are improved.

The invention provides an intelligent research and development system, device and equipment based on Ai and a storage medium, relates to the field of research and development systems, and aims to convert project management from experience driving to data and AI driving so as to greatly improve the accuracy of task allocation, risk identification and progress prediction. The system can automatically monitor, analyze and actively intervene the research and development process, manual intervention is reduced, and the management efficiency is improved; the burden of compiling the report by a project manager is greatly reduced, and the timeliness, the accuracy and the objectivity of the report are ensured; a complete research and development traceability chain enables the project process to be extremely transparent, and audit, problem positioning and knowledge inheritance are facilitated; scattered research and development knowledge is structurally precipitated in a knowledge graph to become digital assets which can be inquired and reused by subsequent projects.

The invention relates to the technical field of project management, and particularly discloses a project management method and system based on an AI large model technology, and the method comprises the steps: collecting multi-dimensional project execution data, carrying out the data cleaning and feature coupling analysis of the multi-dimensional project execution data, and generating a normalized project feature tensor; inputting the task delay risk into a pre-trained time sequence prediction large model, and outputting a task delay risk probability distribution matrix; carrying out risk level label mapping based on the task delay risk probability distribution matrix, and generating a multi-level risk early warning signal; and in response to the risk event exceeding the preset threshold in the multi-level risk early warning signal, a resource redistribution scheme is generated, and a project manager not only can monitor the project progress in real time, but also can quickly adjust resource configuration when the risk occurs, thereby realizing dynamic management. The intelligent project management mode based on data driving not only improves transparency and controllability of the project, but also provides powerful technical support for successful implementation of the project.

The invention relates to the technical field of information technology data processing, and provides an intelligent examination and approval decision-making system and method based on block chain technology change design, which constructs a change process model by obtaining project information and user change demands, and realizes intelligent processing and examination and approval of user change design based on the change process model. The business process data is stored and verified through the block chain technology, and the tampering resistance and traceability of the data are improved; meanwhile, the examination and approval result is verified by using the service examination and approval simulation model, so that the accuracy of examination and approval decision is improved. According to the method, the problems of fragmentation of an approval link, low flow efficiency and the like in an information processing process in the prior art are solved, the safety and transparency of engineering change design management are improved, multi-party cooperative work is promoted, and scientific and efficient decision support is provided for project managers.

The invention belongs to the technical field of IT type project cost financial management, and discloses an IT type project cost financial independent accounting system, which comprises a project management module, a receivable management module, a payable management module, a purchase management module, a financial system data exchange module, a human resource data exchange module and an early warning management module. According to the system, integrated management is adopted, project cost is monitored in real time and dynamically adjusted, the system collects and updates cost data in real time, rapid adjustment is carried out once deviation is found, it is ensured that the cost is controlled within a prediction range, project management flexibility and response speed are improved, cost hyper-branched risks are reduced, and meanwhile through automatic data processing and accounting processes, the project management efficiency is improved. The cost accounting accuracy and efficiency are remarkably improved, personal errors are avoided, manual calculation is simplified, a project manager can efficiently master the cost condition, powerful data support is provided for project decision making, and the scientificity and effectiveness of project management are ensured.

The invention provides a construction informatization management method and system, relates to the technical field of informatization management, and is characterized in that an independent work point is used as a unified space and management unit, and static management information in a building information model and project planning data is converted into static management information; and integrating and associating with real-time dynamic data from heterogeneous systems of personnel, equipment, environment, video monitoring and the like, and automatically judging and visually displaying the comprehensive execution state of each independent work site based on a preset rule. The core step of the method is that a construction site is finely divided into independent work points with independent working procedures and management responsibility, and dynamic and static data deep fusion and state evaluation are carried out by taking the independent work points as basic units, so that the problems of information islands and fuzzy responsibility in traditional construction management are effectively solved. And a real-time, transparent and traceable global command view is provided for project managers, so that the refined and intelligent management level of the construction process is remarkably improved.

The invention relates to the technical field of data monitoring, in particular to a shield tunnel segment operation monitoring method and system based on multi-source data fusion, and the method comprises the steps: obtaining shield tunneling parameters and segment operation state data, processing the shield tunneling parameters and the segment operation state data to obtain a monitoring data file, and transmitting the monitoring data file to a preset service; the preset service processes and analyzes the monitoring data file to obtain a processing and analysis result and sends the processing and analysis result to the business layer; and the business layer provides a plurality of business functions and decision support, carries out data analysis and prediction, evaluates the working state of the shield tunneling machine, and provides necessary information for project management personnel and decision makers. According to the method, the problem of importing multi-source data into a standardized database is solved, the position information of the duct piece can be visually checked, the information of the stratum where the duct piece is located can be online checked, a visual visual interface is provided, and the time consuming problem of data query analysis when the shield monitoring data volume is large is solved.

The invention provides an intelligent bond project establishment application report compiling method and system based on multi-agent cooperative work, and the method and system employ an architecture based on multi-agent cooperative work, can simulate the working process of an actual operator, and cooperatively complete the task decomposition, data arrangement, content generation and structure verification of financial document compiling work. The automation level is improved. A model agent for simulating the division roles of six financial project groups is designed, and the model agent comprises a project manager, data investigation, material examination, content writing, quality control auditing and content correction. Each role plays different functions and tasks in the research and report writing process, uses different tools, and is mutually matched from multiple dimensions, so that the quality and efficiency of the bond project establishment application report are improved.

The invention discloses a BIM-based fabricated building management method, and relates to the technical field of fabricated buildings, and the method comprises the following steps: extracting the type of a prefabricated part, the demand of the prefabricated part, and the use condition of the prefabricated part in a corresponding construction stage through a BIM model through a data collection module; according to the building management method, dynamic factors such as the construction speed and weather influence are considered, accurate prediction of the requirements of the prefabricated parts of the BIM fabricated building is achieved, project managers can better master the supply condition of the prefabricated parts, comprehensive optimization of logistics cost is achieved through accurate calculation of delay cost, and the construction efficiency is improved. According to the technical scheme of the invention, a manager can timely take targeted optimization measures, the direct cost and the indirect cost can be comprehensively analyzed, the comprehensive evaluation of the cost benefit is realized, the project manager can accurately understand the economic benefit and progress control condition of the project, more scientific and comprehensive support is provided for decision making, and an excellent management effect is achieved.

The invention discloses a multi-source information fusion-based comprehensive quality portraying method for small, medium and micro-sized enterprises. The method comprises the steps of S1, constructing a portraying dimension and label classification method; s2, data preprocessing and application; s3, static label extraction and dynamic label establishment; s4, quickly fusing the labels, and matching and classifying; and S5, constructing a scoring and feedback mechanism. According to the method, open information of enterprises and products is collected in modes of comment, application, error correction and the like, the information is verified, the information accuracy is continuously improved, and generated dynamic tags and static tags are fused, so that the generated comprehensive tags are highly associated with enterprise users; by constructing a scoring mechanism, enterprise users can obtain scoring information from the service platform, the service quality, the enterprise comprehensive quality and the product quality are improved, a one-to-one communication platform between an enterprise project principal and a customer is established through a payment channel, and the accuracy of platform interaction and the enterprise comprehensive quality service level are improved.

The invention discloses a project task dependency relationship intelligent modeling system and method based on a knowledge graph, and belongs to the technical field of project task modeling, and the method specifically comprises the steps: obtaining project task image data, carrying out the preprocessing of the obtained project task image data, and according to the preprocessed project task image data, carrying out the intelligent modeling of the project task dependency relationship; the method comprises the steps of constructing a preliminary project task knowledge graph, analyzing direct and indirect dependency relationships between project tasks, updating the preliminary project task knowledge graph to obtain the project task knowledge graph, and optimizing project task scheduling based on the project task knowledge graph and in combination with attribute information of the project tasks. The priority and resource allocation of project task execution are determined, and project task nodes and dependency relationships in the knowledge graph are automatically updated based on real-time data and project progress; the priority and resource allocation between project tasks can be processed in real time, so that a project manager can obtain the latest dependency relationship and progress condition of the tasks in real time.

The application discloses a task allocation method and system based on artificial intelligence, and the method comprises the following steps: obtaining the meeting content of a project manager and analyzing the voice information corresponding to the meeting content, obtaining multiple to-be-allocated tasks according to the voice information; dividing each to-be-allocated task into multiple levels of subtasks according to the task index of each to-be-allocated task; determining the allocation subtasks of each participant through an artificial intelligence model according to the experience information and enterprise professional level information of the participant and the execution complexity of each subtask; and determining the personnel allocation situation of each to-be-allocated task according to the membership relationship between the allocation subtasks of each participant and the multiple to-be-allocated tasks. The method can avoid subjective personnel allocation by the project manager, save a large amount of allocation time, improve practicability, guarantee the objectivity of the task personnel allocation result, and make the personal ability of each person suitable for the allocated task.

The invention discloses a man-hour filling and reporting method, system and device and a medium, and the method comprises the steps: building a user man-hour filling and reporting list with a user as a role, and pushing the user man-hour filling and reporting list to a corresponding user; receiving a user man-hour list formed by a user based on the user man-hour filling list; summarizing the user working hour lists to form a summarized approval list; and pushing the summarized approval sheet to the corresponding approver, so that the approver performs man-hour approval. According to the method, the user is taken as a main body to push the man-hour filling sheet, the filling efficiency of the man-hour filling sheet can be improved, the pushing of a manpower department and a project manager is not needed, and manpower resources and time resources required by man-hour filling are reduced. And meanwhile, after the user working hour list is received, the user working hour list is summarized and pushed to the supervisor for examination and approval, so that the supervisor can obtain the working hour information of each employee in time, and the use efficiency of enterprise resources and the human resource occupation condition of each project can be known in time.

The invention provides a project resource analysis method and device, equipment, a medium and a program product. The method comprises the steps that a trigger instruction of resource analysis is received, an analysis interface is displayed, and the analysis interface comprises a problem input area and an analysis display area; in response to a reference instruction received in the question input area, a reference interface is displayed, and the reference interface comprises at least one reference content; in response to a reference operation on a target reference content in the at least one reference content, adding the target reference content to a resource analysis problem of the problem input area; and in response to sending of the resource analysis problem, displaying a resource analysis result corresponding to the resource analysis problem in the analysis display area. According to the invention, the resources can be analyzed through the large model in project management, the current situation and problems of the project resources can be accurately known, and valuable insight is provided for project managers.

The present invention discloses a method for assessing the risk of construction project shutdowns based on rainfall indicators. By establishing a forecast model with actual precipitation and a 24-hour precipitation forecast as input conditions and the shutdown risk level as the output result, and matching corresponding response measures, a risk forecast text can be formed. When the actual precipitation and forecast precipitation data exceed the pre-set threshold indicators, the start-up conditions are met, and then the forecast model provides alarm information based on the actual situation and early warning information based on the forecast, so that project managers can make scientific decisions, improve the risk resistance of construction projects, and reduce losses caused by meteorological influences. The present invention solves the problem that project managers at existing construction sites rely on experience to deal with various types of weather, cannot make scientific decisions, and easily cause losses to the project.

The invention relates to the technical field of big data, in particular to a project management intelligent analysis early warning method based on big data, which comprises the following steps: acquiring structured data, unstructured data, behavior data and environment data related to a project; based on the structured data, the unstructured data, the behavior data and the environment data, constructing a dynamic knowledge graph; generating an intelligent early warning decision matrix according to the dynamic knowledge graph; based on the intelligent early warning decision matrix, project risk early warning information and decision suggestions are output, through organic combination of technologies such as data fusion, dynamic modeling, multi-layer early warning, intelligent decision and innovative visualization, intelligence and refinement of project management are realized, and the method not only can greatly improve efficiency and precision of project risk management, but also can greatly improve project risk management efficiency and accuracy. And comprehensive, in-depth and operable decision support can be provided for project managers, so that the risk of project failure is remarkably reduced, and the project success rate is improved.

The present invention relates to the technical field of information transmission of engineering supervision platforms, and discloses an information transmission method and system based on an engineering supervision platform, including: obtaining construction data uploaded by on-site supervisors, implementing a classification compression preprocessing strategy to classify, compress, and perform robust coding on the construction data; according to an execution key and the construction data, implementing a double-layer encryption strategy to generate a digital signature, and encrypting the construction data, the execution key, and the digital signature; sending the encrypted construction data, execution key, and digital signature to project managers through a network transmission path; implementing a fault monitoring strategy for each node in the network transmission path to determine whether the node is faulty; if a faulty node is detected, implementing a multi-level redundant backup strategy to replace the faulty node with a backup node; implementing a hierarchical handling strategy for abnormal network behaviors to maintain the security of the network transmission path, improving the efficiency and security of data transmission.

1. Name of the designed product: Jacket (project management). 2. Use of the designed product: Clothing for project managers to wear in various scenarios. 3. Design points of the designed product: Combination of shape and pattern. 4. Picture or photo that best indicates the design points: Front view. 5. The designed product is a thin product, and other views are omitted.

The invention relates to an amphibious multi-business and multi-mode complete-period construction project cost management and control system. The system comprises a project income management module, a project budget management module, a project planning management module, a project cost management module, an economic activity analysis module and an assessment and evaluation module. According to the invention, big data, artificial intelligence, mobile internet and other informatization technologies are applied to perform full-business process management and control on project income, budget, planning, cost and economic activity analysis, and by means of dynamic assessment and evaluation, the cost management and control requirements of construction projects of different types, different stages and different conditions are met, so that the cost management and control requirements of construction projects on water or land are met. The cost management and control requirements of the project can be met whether a standard project or an EPC project, the universality of the system is improved, meanwhile, a data flow mechanism with data communicated layer by layer is constructed through strict system logic, the reuse rate of process achievements is improved, the burden of data filling and reporting can be reduced for first-line project management personnel, and the working quality and efficiency are improved.