550 results about "Construction planning" patented technology

The invention discloses a construction progress control method in project supervision, and the method comprises the steps: calculating the current punctual completion rate and process handover delay time of each subpackage provider according to a real-time progress data set and a pre-established project network diagram, recognizing the progress fluctuation modes of different project stages through a time sequence analysis method, and carrying out the construction progress control according to the progress fluctuation modes. Establishing a correlation model of the sub-packaging quotient and the engineering stage; according to the priority scores, taking minimization of overall construction period delay and resource idleness as objective functions, applying an optimization algorithm, dynamically adjusting a construction plan and a resource allocation scheme of each subpackage provider, and generating an optimized project progress plan which comprises specific work arrangement and resource allocation suggestions of each subpackage provider; a successful coordination strategy in a historical project is analyzed, coordination measures are recommended for project management personnel and a set of communication matrix is generated according to characteristics and progress conditions of a current project, and the coordination measures comprise resource allocation suggestions, process optimization schemes and communication strategy templates.

The invention relates to the technical field of intelligent building management, in particular to a construction site comprehensive management system based on machine vision, which comprises an image capturing and partitioning module, a construction state analysis module, a component progress matching module, a progress deviation analysis and early warning module, a task dynamic allocation module and a construction node optimization module. According to the invention, through regionally extracting and numbering image data and combining a position coordinate subdivision technology, accurate partitioning and ordered data organization of a construction site are realized, the structural property and traceability of image data are guaranteed, real-time image analysis is carried out to compare the image data with a construction plan, the state of a component is identified, and progress deviation is revealed; a dynamic early warning mechanism is established, abnormal areas are marked, risks are prompted in advance, resource allocation is concentrated in key areas based on real-time progress and task priorities, task distribution and resource use priorities are optimized, reasonable and efficient allocation of resources is achieved, and therefore intelligence, reliability and safety of construction management are improved.

The invention relates to the technical field of data processing, and discloses an intelligent bridge reinforcement decision generation method, device and equipment based on damage identification. The method comprises the following steps: carrying out bridge damage identification and evaluation on a bridge state data set to obtain a bridge damage characteristic spectrum; performing intelligent decision analysis on the bridge damage characteristic spectrum, generating a preliminary reinforcement scheme, and obtaining a candidate reinforcement strategy set; performing parametric modeling and multi-scale simulation on the candidate reinforcement strategy set, and performing coupling calculation evaluation on a reinforcement effect to obtain an optimized reinforcement scheme; virtual construction planning is conducted on the optimized reinforcement scheme, a construction process model is generated through an intelligent scheduling algorithm, and a target construction scheme is obtained; and monitoring and feeding back the target construction scheme in real time, and dynamically optimizing the construction process through an adaptive control algorithm to obtain a target intelligent reinforcement implementation scheme. The intelligent bridge reinforcement decision generation efficiency and accuracy based on damage identification are improved.

The invention discloses an engineering project progress multi-dimensional monitoring system and method based on an information technology, and belongs to the field of monitoring. The engineering project progress multi-dimensional monitoring system comprises an initial construction plan construction module, a data acquisition and environment monitoring module, a data analysis and plan optimization module, a construction progress prediction module and a risk management module. By collecting multi-dimensional data of a construction site in real time and applying the intuitionistic fuzzy reasoning algorithm, a construction plan can be dynamically adjusted to cope with constantly changing site conditions and external environment factors, the intuitionistic fuzzy reasoning algorithm is utilized to analyze requirements and bottlenecks of a construction project, and the construction efficiency is improved by combining construction logic and physical constraints. Resource configuration can be carried out more accurately; fuzzy and uncertain conditions are processed through the fuzzy logic controller, it is ensured that a project meets all related building and safety standards, and project quality and safety are ensured through continuous monitoring and timely adjustment.

The invention discloses an electric power capital construction site operation environment data monitoring and safety management method, which belongs to the field of intelligent decision technology and electric power safety management, and comprises the following steps: constructing a semantic network framework according to a construction plan; collecting and calibrating multi-source environment data to generate a trusted data set; generating a real-time risk network graph based on the semantic framework and the trusted data set; calculating a robust risk index and performing sensitivity deconstruction; generating a closed-loop intervention instruction when the risk indicator exceeds a safety threshold; and finally, collecting, feeding back, iteratively optimizing the whole system, and generating a cross-project multiplexing intelligent template library. According to the method, a comprehensive technical path of semantic modeling, causal inference and closed-loop adaptive optimization is adopted, the operation situation can be deeply analyzed, potential risks can be quantified and attributed prospectively, the optimal intervention strategy is intelligently generated, and the intelligence, precision and prospective level of safety management of the electric power capital construction site is remarkably improved.

The invention discloses a BIM technology-based comprehensive pipeline construction management system, which relates to the technical field of construction management and comprises a BIM model creation module, a pipeline construction planning module, a real-time progress monitoring module, a pipeline conflict detection and optimization module and a quality and safety management module. According to the comprehensive pipeline construction management system based on the BIM technology, multiple problems existing in traditional construction management can be effectively solved, through the functions of visual display, conflict detection and optimization, real-time progress monitoring, potential safety hazard inspection and the like of the BIM model, the system provides a comprehensive management tool for the construction process, and the construction efficiency is improved. The construction efficiency is improved, resource allocation is optimized, the construction quality and safety are greatly improved, finally, by means of the system, the overall management level of a project is remarkably improved, and the construction progress, quality and cost are more accurately and effectively controlled.

The invention relates to the field of construction planning visualization, in particular to a construction planning visualization method and system for a refuse transfer station. The method comprises the following steps: acquiring a satellite positioning map and a refuse transfer station design drawing of a to-be-developed area; image detail reconstruction is carried out on the satellite positioning map, road space distribution fitting is carried out, and a regional road distribution network is constructed; performing surrounding building positioning calculation on the detail optimization reconstruction satellite image based on a regional road distribution network, performing an optimal site selection decision, and extracting an optimal address region image; carrying out transfer station key feature point identification on the refuse transfer station design drawing, then carrying out three-dimensional point cloud modeling, and constructing a transfer station three-dimensional structure model; and according to the optimal address area image, carrying out corresponding foundation accurate matching on the transfer station three-dimensional structure model, carrying out spatial positioning mapping, and constructing a transfer station address twinborn model. According to the method, the operation efficiency of the transfer station is improved, and the rationality of building planning is enhanced.

The invention discloses a building robot task planning and skill learning method and system, and relates to the technical field of intelligent construction and building robot control, and the method comprises the steps: receiving construction target description and construction environment information through a multi-modal task-skill collaborative generation model; and generating a structured semantic vector and reasoning a construction planning graph containing a plurality of subtasks. And collecting operation behavior parameters of the building robot in each subtask according to the construction planning graph, constructing an operation sample, and inputting the operation sample into the multi-modal task-skill collaborative generation model for skill learning and action instruction generation. And in the construction execution process, various sensing data are fused for real-time judgment, and if the task execution state is inconsistent with the planning state, the multi-mode task-skill collaborative generation model adjusts an instruction based on the latest state and outputs a reasoning chain. According to the method, the deployment efficiency and task adaptability of the robot system in actual construction are improved, and a foundation is laid for man-machine cooperation and unmanned construction in the field.

The invention relates to the technical field of artificial intelligence, in particular to a charging pile construction planning method and system based on artificial intelligence. The method comprises the following steps: acquiring existing power infrastructure data and multi-source heterogeneous data, wherein the multi-source heterogeneous data comprises traffic data, geographic data, vehicle data and charging behavior data; performing time sequence feature extraction on the multi-source heterogeneous data, and performing cross-time scale fusion on different data source features by using a preset hierarchical attention network model to obtain factor weight data; and constructing a long-term charging demand prediction model through a sequence-to-sequence model according to the factor weight data and the multi-source heterogeneous data. According to the site selection method based on the risk minimum set coverage problem, initial site selection scheme data is generated by combining multi-objective optimization of the coverage rate, the service radius and the accessibility, and more scientific charging pile layout is achieved.

The invention provides a prefabricated pipe pile construction total factor intelligent management method and system based on the digital twinborn technology, and relates to the technical field of construction management, a three-dimensional model is established through the BIM technology, pipe pile attributes are bound, construction data are collected in real time through the Internet of Things, and a dynamic digital twinborn body is formed. Through integration of an API interface and a project management platform, an AI algorithm is used for analyzing data, resource allocation and construction plans are dynamically adjusted, instructions are optimized and pushed to the site, construction efficiency and installation precision are improved, and the problems that traditional management is low in efficiency and large in error are solved.

The invention provides an intelligent building construction management system and method based on BIM scene construction, and relates to the technical field of building construction management. In the construction process, the management system collects mass data in real time by means of sensing layers spread all over key nodes of a construction site; the method comprises the following steps of: transmitting operation parameters of construction equipment, operation dynamics of constructors, consumption rate of materials and change of a field environment to a data processing center, accurately positioning a low-efficiency waiting problem existing in a material transfer link through deep analysis of a big data processing engine and an artificial intelligence algorithm library, recommending an optimization scheme, and improving the efficiency of material transfer. According to the method, the hoisting sequence is adjusted, unnecessary working hour loss is reduced, by means of a BIM model platform, a construction plan is presented in a visual mode, and the management system can rapidly generate and recommend and flexibly deploy construction team personnel, optimize the construction process sequence, ensure construction coherence, reduce construction delay and shorten the construction period.

The invention relates to the technical field of civil engineering, in particular to a karst development area cast-in-situ bored pile construction method which comprises the following steps: based on construction position information, collecting electromagnetic wave data of a target area at multiple angles and depths, and recording rock layer, karst cave and crack data to obtain geological data of the target area. According to the method, a data basis is provided for geological three-dimensional model construction by utilizing electromagnetic wave data and identifying a rock layer, a karst cave and a crack, the prediction precision of the model is improved by simulating the response of karst, a fault and a soft soil layer to a structure, and the prediction accuracy of the model is improved by combining the evaluation of chemical erosion and physical erosion effects of a target karst development area on the cast-in-place pile. The long-term influence of the environment on the pouring material is predicted, the stability and safety of the structure are improved, the long-term sustainability of a target engineering project under the karst complex geological condition is ensured, and the scientificity and efficiency of construction planning are improved by combining drilling position analysis and construction path planning.

The invention belongs to the technical field of construction planning, and particularly relates to a power grid transmission line construction scheme planning method and system based on a knowledge graph, and the method comprises the steps: firstly constructing a knowledge graph model of a mechanical construction scheme and a standardized adaptation principle; obtaining a power transmission line project construction task, constructing a construction data integration set, inputting the construction data integration set into the mechanical construction scheme knowledge graph model, generating a power transmission line mechanical construction scheme, and screening out a standardized construction scheme based on an optimized MOPSO algorithm; according to the method, the knowledge graph and the three-dimensional construction scene are constructed, the multi-target problem is solved by optimizing the MOPSO algorithm, the optimal construction scheme is obtained, the construction process is simulated, the construction process is optimized, and the construction efficiency is improved. Therefore, standardized processing of different construction projects is achieved, the construction efficiency is improved, and the construction quality is guaranteed.

The invention relates to the technical field of construction project management, in particular to a construction project management system based on cloud computing, which comprises a construction path optimization module, a construction state analysis module, a construction environment monitoring module, a progress plan adjustment module and a green construction optimization module. According to the method, through combination of construction task resource distribution and three-dimensional space information, resource path distribution logic is optimized, material consumption, equipment operation states and key process deviation data are utilized, accurate positioning and prediction of construction dynamic problems are realized, construction interruption is reduced, and equipment and personnel distribution characteristics are extracted based on field image data, so that construction efficiency is improved. The equipment arrangement deviation degree and the potential safety hazard superposition value are quantified, the safety and efficiency of a construction site are improved, and the utilization rate of green construction resources is improved by dynamically adjusting the process time and the resource utilization rate, optimizing the relation between task nodes and factors, improving the flexibility and the response capability of a construction plan and conducting partition modeling energy consumption data and multi-constraint optimization.

The invention discloses a bridge management and maintenance decision-making system and method based on multi-agent collaborative optimization, and the system comprises a monitoring agent which is deployed in a cloud server and is used for obtaining abnormal data in a bridge structure and environment data; the diagnosis agent is used for evaluating the health state of the bridge by utilizing a built-in knowledge base, a built-in machine learning model and a built-in physical model based on the abnormal data; the decision-making agent is used for generating a plurality of candidate maintenance schemes based on an evaluation result, and screening out an optimal scheme by integrating the comprehensive utility of each scheme and the resource matching degree score of the resource scheduling agent on each scheme; the resource scheduling agent generates a construction plan according to the optimal scheme; the coordination / communication agent is used for ensuring efficient cooperation among the agents through a communication protocol and a negotiation mechanism among the agents; the diagnosis report, the optimal scheme and the construction plan are integrated and presented to a bridge manager through a human-computer interaction interface; and collaborative optimization of bridge management and maintenance decisions is realized through continuous feedback and self-learning.

The invention discloses an unmanned aerial vehicle infrastructure construction supervision method and system based on 5G, and belongs to the field of unmanned aerial vehicle monitoring. The unmanned aerial vehicle infrastructure construction supervision system comprises an unmanned aerial vehicle module, a 5G communication module, a data processing module, a cloud storage module, a mobile terminal module, a system management module and a visual management module; the unmanned aerial vehicle module is provided with a high-definition camera, an infrared sensor and a laser range finder, and high-quality construction site data is obtained; the data processing module processes and analyzes the data acquired by the unmanned aerial vehicle; the visual management module compares data acquired by the unmanned aerial vehicle with a construction plan, can generate a real-time visual chart of the construction progress, and displays the construction progress to a supervisor in a visual manner; real-time image transmission is achieved through the system, supervisors can know the progress condition of a project in real time, discover problems in time and take corresponding measures, construction efficiency and quality are improved, and cost and risks are reduced.

The invention relates to the field of constructional engineering, and discloses an intelligent construction management and control method for constructional engineering, which comprises the steps of collecting multi-dimensional data of a building construction site, including construction progress data, personnel positioning information, an equipment operation state and site environment parameters, and constructing a construction behavior feature data set in combination with a multi-source data fusion algorithm; performing automatic structured analysis on the construction behavior feature data set, constructing a construction process modeling framework based on a hierarchical feature clustering method, and introducing a dynamic feedback learning mechanism to perform adaptive optimization on a modeling result; judging whether the optimization process is stable or not according to the evolution trend of the process model, and if so, recording the stage state of the current construction process feature; and based on the corrected construction plan path, performing disturbance factor correction on the prediction progress by applying a multi-scale construction simulation algorithm, extracting corresponding control parameters, and performing intelligent adjustment on prediction nodes. The method has the advantage of improving intelligent construction management.

The invention discloses a building robot multi-machine cooperative construction planning method and system, and belongs to the technical field of building construction automation, and the method comprises the steps: collecting three-dimensional space data of a construction site, combining with a timestamp, constructing a four-dimensional space-time semantic map, recognizing a process stage, dynamically allocating tasks, generating an initial path through an improved A * algorithm, and constructing a three-dimensional space-time semantic map. And the path is adjusted in real time by adopting a dynamic window method. According to the three-dimensional collaborative modeling design method of the building robot, the problem of dynamic environment adaptability is solved through combination of four-dimensional map construction, Nash equilibrium allocation and an improved A * algorithm.

The invention relates to the technical field of collaborative construction, in particular to a collaborative construction method and system based on BIM, and the method comprises the following steps: obtaining component information and a construction path, calculating the center distance, the number of intersection lines and the blocking ratio, evaluating the density and the staggering degree, generating an urgent distribution set and a task list, extracting spatial parameters, and calculating the overlapping level. And judging the compression feasibility of the time window, and generating a non-parallel task list. According to the method, through quantitative evaluation of blocking risks between construction nodes, a dynamic sorting list generated based on urgency degree values and construction plan binding tasks, conflict levels between component pairs are divided through an operation space overlapping degree index, compression judgment is performed on an adjustable time window, and a minimum interference construction time period is allocated; strong interference task pairs are calibrated to avoid parallel construction, the sorting rationality of construction tasks and the space decoupling efficiency of job scheduling are effectively improved, and fine matching and efficient cooperation of component scheduling sorting and resource allocation in a dynamic scene are achieved.

The invention relates to an intelligent construction method and system based on Internet of Things monitoring, and the method comprises the steps: obtaining real-time vibration spectrum data and historical equipment vibration data of target construction equipment, carrying out the environment noise suppression of the real-time vibration spectrum data based on the historical equipment vibration data, and obtaining equipment noise reduction state features; obtaining an operation vibration waveform of the impact equipment, and carrying out equipment health degree analysis on the noise reduction state characteristics of the equipment to obtain a health degree attenuation rate; carrying out equipment load reduction operation quantification on the health degree attenuation rate based on a preset construction plan, and carrying out equipment safety collaborative analysis to obtain an associated equipment collaborative scheduling strategy; and performing instruction construction on the target construction equipment according to the associated equipment collaborative scheduling strategy to obtain a load control instruction, and performing construction optimization on the construction plan to obtain an optimized construction plan. According to the invention, the equipment health degree attenuation rate can be dynamically analyzed based on the operation vibration waveform of the impact equipment, and real-time response to the equipment performance change is realized.

The invention relates to the technical field of construction progress collaborative management, in particular to a multi-source data driven construction progress intelligent collaborative control method and system. The method comprises the following steps: acquiring multi-source data of a construction site; dynamically fusing the multi-source data to obtain a three-dimensional construction map; constructing a construction plan planning model, and generating an optimal construction plan by using the construction plan planning model based on the three-dimensional construction map; and performing dynamic resource scheduling and allocation according to the optimal construction plan to obtain a resource allocation scheme. According to the method, the three-dimensional construction map is constructed by fusing the multi-source data, then the construction plan planning model is constructed to obtain the optimal construction plan, and finally resource allocation is performed based on the optimal construction plan, so that the problems of data islands, progress lag and response lag in traditional highway engineering construction are solved, and the construction efficiency and safety are remarkably improved.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for a multi-modal artificial intelligence platform for building construction. The multi-model artificial intelligence platform includes various engines that perform various computer-implemented methods. The various engines include a site selector artificial intelligence (AI) engine, a geospatial database, a site compliance analyzer AI engine, a masterplan generator AI engine, a compliance analyzer AI engine, an aesthetic generator AI engine, a schematic generator AI engine, a construction plan generator AI engine, a project timeline generator AI engine, a compliance application generator AI engine, and a financial model generator AI engine. Respective AI engines collaboratively cooperate for end-to-end AI-driven building construction design and development.

The invention relates to the technical field of data processing, and provides a BIM-based building construction progress management method and system, and the method comprises the steps: carrying out the decomposition of a BIM model into a component set according to the construction process of a building, and building the construction plan mapping of each component; the method comprises the following steps: collecting construction site data of a building, and preprocessing the construction site data to obtain preprocessed data; processing the preprocessed data through a progress recognition model to obtain the actual construction progress of the building; calculating the deviation between the actual construction progress and the planned construction progress of the building; according to the deviation between the actual construction progress and the planned construction progress of the building, a multi-objective optimization model is combined to adjust the construction plan to obtain a target construction plan; and performing construction progress management on the building based on the target construction plan. According to the invention, the accuracy and the intelligent degree of building construction progress management can be improved.

The invention relates to the field of municipal communication pipelines, and discloses a municipal communication pipeline-based laying construction management system, which comprises the following steps of: acquiring images, position information and voice data of a construction site, preprocessing the acquired content by utilizing a lightweight edge calculation model, and judging whether data exception exists or not; on the basis of spatio-temporal information matching and an image content recognition algorithm, construction data collected on site are compared with the engineering plan model, and whether areas which are not constructed according to specifications are recognized or not is judged; uniformly converting the unstructured data into construction record items in a standard format by using a multi-modal feature fusion method, and judging whether the unstructured data is successfully converted or not; dynamically updating a construction progress state in combination with a project construction plan and real-time acquired data, and generating a visual Gantt chart display; and training the historical engineering data based on a machine learning model, and automatically pushing early warning information to a management terminal. The method has the advantage of improving the communication pipeline construction management capability.

The invention discloses a digital twin model driven photovoltaic field construction transportation system and method, and belongs to the technical field of photovoltaic field construction. The system comprises a digital twin module, a construction planning and design module, a monitoring and management module and an interaction module. The digital twinning module constructs a three-dimensional digital twinning model; the construction planning and design module generates a candidate construction material transportation path scheme and a candidate construction equipment scheduling scheme based on a photovoltaic field construction transportation objective function; driving the digital twin model to execute a simulation task, and adjusting the candidate construction material transportation path scheme and the candidate construction equipment scheduling scheme based on a simulation result; the monitoring and management module generates a monitoring result based on the real-time monitoring data of the construction site of the photovoltaic field area; and the interaction module provides information of a photovoltaic field construction site for a user. The construction efficiency is improved, the construction cost is reduced, quality control is achieved, and construction safety and flexibility are guaranteed.

The invention, which relates to the technical field of mineral product screening, discloses an intelligent construction management platform for city updating, comprising the following steps: establishing a unified data standard and a data interface protocol to ensure that data of different systems, departments and enterprises in the platform can be seamlessly jointed; according to the invention, through unifying the data standard and the interface protocol, data sharing of different systems is realized, and project management efficiency and decision accuracy are improved. The real-time data acquisition and intelligent analysis technology enhances the safety monitoring and intelligent early warning functions, and ensures that potential safety hazards in the construction process are recognized and processed in time. Meanwhile, the flexibility and the emergency response capability of the project are improved by a dynamic adjustment and intelligent early warning mechanism, resources and construction plans can be automatically adjusted in the progress of the project, emergency problems can be dealt with, progress delay and resource waste are reduced, and smooth progress of the project is guaranteed.

The invention relates to the technical field of lean construction management, in particular to a BIM (Building Information Modeling) technology-based reservoir lean construction management method and system. The method comprises the following steps: acquiring admission material message data and real-time sensor data; performing data preprocessing on the admission material message data, and performing physical data set association through a preset BIM model to generate a BIM reservoir construction model data set; performing real-time data endowing on the BIM reservoir construction model data set by using real-time sensor data, and generating a reservoir construction-planned twin model; therefore, by integrating multi-source data, real-time monitoring and dynamic optimization are realized, the problems of information lag and untimely response in traditional construction management are solved, and the safety and efficiency of the reservoir construction process are improved.

The invention provides a building construction site material demand sensing method and device based on AI prediction, and relates to the technical field of building data processing. The method comprises the following steps: obtaining construction plan information, construction site pictures, construction environment data and historical construction information of a historical period of time of a target building construction project; obtaining the actual construction progress of the target building construction project based on the construction site picture; performing construction progress prediction based on the actual construction progress, the construction environment data and the historical construction information to obtain a predicted construction progress of the target building construction project in a future time period; based on the predicted construction progress and the construction plan information, determining predicted construction resistance of the target building construction project in a future time period; and inputting the predicted construction progress and the predicted construction resistance into a preset material prediction model based on machine learning to obtain a material demand sensing result of the target building construction project in the future time period. According to the invention, material requirements can be accurately sensed in combination with specific building construction projects.

The invention provides a power construction monitoring method and system. The power construction monitoring method is used for performing remote monitoring on a construction plan to be performed by a constructor, and comprises the following steps: S1, the constructor obtains a current construction site based on a smart watch, and sends the construction site to a construction monitoring server; s2, in response to the received construction site, the construction monitoring server retrieves a construction plan corresponding to the construction site from a preset construction plan library; and S3, based on the retrieval result, the construction monitoring server sends a construction permission message to the smart watch. Through on-site data acquisition and analysis and comparison of a remote server, automatic compliance judgment on construction operation is realized, and the risk of manual wrong operation is eliminated; and the state of the constructor is remotely monitored in the construction process, so that whether the state of the constructor is abnormal or not can be known in time.

The invention relates to a building construction cost control method, system and device and a medium, and relates to the technical field of engineering cost, and the method comprises the steps: analyzing a plurality of waste images collected from a waste stacking area to recognize the types of wastes, and carrying out the statistics of the number of each type of wastes; constructing a three-dimensional model of the current construction project according to the real-time condition of the construction site, comparing the three-dimensional model with a preset construction plan model, obtaining the expected consumption of various materials matched with the three-dimensional model at the current construction stage, and calculating the rejection rate of each type of materials; and judging whether each material exceeds a preset rejection rate threshold value or not, if so, searching the place source of the waste corresponding to the rejection rate of the material, calculating the loss cost, and sending out a cost abnormity early warning and a construction abnormity early warning. The manufacturing cost can be controlled by controlling the rejection rate of engineering materials, and the increase of the manufacturing cost caused by the increase of waste is reduced.