Gis-based municipal facility whole life cycle management method and system

Abstract

The application provides a GIS-based municipal facility whole life cycle management method and system, and belongs to the technical field of smart city municipal management. The method comprises the following steps: performing field splitting and attribute classification processing on standardized municipal facility basic data to generate a multi-dimensional asset feature set; performing space-time correlation matching processing on the multi-dimensional asset feature set to generate asset space-time binding label data; performing cross-department data completion on the asset space-time binding label data to generate whole-attribute asset mapping data; and through whole-chain connection of asset global unique code and GIS space-time binding, smooth flow of cross-department data can still be realized under the original framework of multi-department independent management, the long-existing data island phenomenon is effectively broken, and the collaborative efficiency of municipal facility management is greatly improved.

Description

Technical Field

[0001] This invention proposes a GIS-based method and system for the full lifecycle management of municipal facilities, belonging to the field of smart city municipal management technology. Background Technology

[0002] Currently, the management of municipal facilities in China has long adopted a departmental, independent construction and management model. Functional lighting falls under the municipal power department, landscape lighting under the urban management department, drainage facilities under the water resources department, and manhole cover facilities under the urban management department. Each department's supporting management system is deployed independently, and the GIS module is only used as a static asset positioning tool, without being deeply integrated with actual business processes. The construction stages of different departments cannot be coordinated, which not only affects the implementation effect of facilities but also wastes public resources. The lack of unified constraints in the construction, management, and maintenance stages has led to long-standing problems such as aging and loss of equipment and facilities.

[0003] The existing management model relies on manual inspections or user reports to trigger maintenance actions. It does not integrate dynamic monitoring data such as water level, leakage current, manhole cover status, and lighting rate. After a fault occurs, it is impossible to quickly determine the scope of impact. Some single-function monitoring systems can only perform basic emergency operations on local equipment and cannot link related facilities and cross-departmental handling processes, which can easily lead to secondary accidents.

[0004] Data from the planning, construction, operation and maintenance, and decommissioning stages are isolated from each other. Problems discovered during operation and maintenance, such as insufficient control box capacity and conflicts with underground pipelines, cannot be relayed back to the early planning stages, resulting in a persistently high rate of project duplication. Most publicly available general GIS municipal management solutions remain at the level of basic ledger display, failing to integrate specific business features such as brightness control, lighting rate analysis, and multi-tenant management of light poles, thus having a low degree of matching with the actual business needs of urban lighting authorities. Summary of the Invention

[0005] This invention provides a GIS-based method and system for the full lifecycle management of municipal facilities, in order to solve the problems mentioned in the background section above: The present invention proposes a GIS-based method for the full lifecycle management of municipal facilities, the method comprising: S1. Standardize the format of the original municipal facility ledger data uploaded by various business departments in the city, remove duplicate items and clean up invalid fields to generate standardized basic municipal facility data; perform field splitting and attribute classification on the standardized basic municipal facility data, extract facility category keywords, spatial coordinate keywords and business stage keywords to generate a multi-dimensional asset feature set; perform spatiotemporal correlation matching on the multi-dimensional asset feature set, use the spatial anchoring technology in the unified GIS base to complete the one-to-one binding of facility entities with geographic coordinates, map the binding results to the preset full life cycle data framework, and generate asset spatiotemporal binding label data; perform cross-departmental data completion on the asset spatiotemporal binding label data, supplement the facility association attribute information that is not synchronized by different business departments, and generate full attribute asset mapping data. S2. Perform business flow transformation processing on the full-attribute asset mapping data, transforming the scattered asset data at each stage into standardized business node data that can be called across links, generating full-cycle business node data; perform scenario adaptation analysis on the full-cycle business node data, and select the processing model type that matches the current business node from the preset scenario model library to generate scenario model matching data. S3. Perform business boundary delineation on the scene model matching data, and limit the processing range of each matching model by combining facility category, spatial range and business stage, and generate processing range limit data for each scene model; arrange the execution order of the processing range limit data of each scene model to generate scene model call priority sequence data. S4. Perform computational resource allocation processing on the priority sequence data of scene model calls, allocate independent running channels and data cache space to each scene model, and generate model resource pre-allocation data; prepare the model resource pre-allocation data for parallel operation and generate a multi-model parallel call ready signal; S5. Perform planning phase data loading processing on the running tasks corresponding to the multi-model parallel call ready signals, overlay and replay regional terrain data, road network planning data, and lighting brightness demand data to generate facility layout pre-simulation data; perform construction phase synchronization processing on the facility layout pre-simulation data to complete the real-time uploading of asset addition information, coordinate update information, and attribute change information during construction, and generate dynamic synchronization data of the construction process. S6. Perform joint processing of dynamic synchronous data during the construction process and operation and maintenance phases, and access real-time IoT monitoring data such as water level, leakage current, manhole cover status, and lighting rate to generate cross-facility joint early warning data; perform backtracking processing of cross-facility joint early warning data during the scrapping phase, complete the registration of spatial resource release after facility demolition, archive residual value information, and retain historical full-cycle data to generate full life cycle closed-loop archived data.

[0006] The present invention proposes a GIS-based full lifecycle management system for municipal facilities, the system comprising: One or more processors; Memory, used to store one or more programs; Wherein, when the one or more programs are executed by the one or more processors, the one or more processors are made to implement the method described in any one of the above.

[0007] The beneficial effects of this invention are as follows: By establishing a complete chain of globally unique asset authorization and GIS spatiotemporal binding, it enables smooth cross-departmental data flow even under the existing architecture of independent construction and management by multiple departments. This effectively breaks down the long-standing data silos and significantly improves the collaborative efficiency of municipal facility management. Simultaneously, the closed-loop data linkage throughout the entire lifecycle from planning to decommissioning allows facility defects discovered during the operation and maintenance phase to directly inform the early planning stages, greatly reducing the rate of redundant construction in municipal projects. In the event of sudden failures, the cross-facility linkage early warning mechanism can quickly correlate the status of surrounding facilities, effectively preventing secondary accidents caused by single facility failures. It covers the management needs of various facilities such as urban lighting, drainage, and manhole covers, and is also adaptable to specific business scenarios such as brightness control and multi-tenant management of light poles, comprehensively improving the granularity of municipal facility management throughout its entire lifecycle. Attached Figure Description

[0008] Figure 1 This is a diagram illustrating the steps of the method described in this invention; Figure 2 This is a detailed flowchart of step S1 in this invention. Detailed Implementation

[0009] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0010] One embodiment of the present invention, such as Figure 1 As shown, a GIS-based method for the full lifecycle management of municipal facilities includes: S1. Standardize the format of the original municipal facility ledger data uploaded by various business departments in the city, remove duplicate items and clean up invalid fields to generate standardized basic municipal facility data; perform field splitting and attribute classification on the standardized basic municipal facility data, extract facility category keywords, spatial coordinate keywords and business stage keywords to generate a multi-dimensional asset feature set; perform spatiotemporal correlation matching on the multi-dimensional asset feature set, use the spatial anchoring technology in the unified GIS base to complete the one-to-one binding of facility entities with geographic coordinates, map the binding results to the preset full life cycle data framework, and generate asset spatiotemporal binding label data; perform cross-departmental data completion on the asset spatiotemporal binding label data, supplement the facility association attribute information that is not synchronized by different business departments, and generate full attribute asset mapping data. S2. Perform business flow transformation processing on the full-attribute asset mapping data, transforming the scattered asset data at each stage into standardized business node data that can be called across links, generating full-cycle business node data; perform scenario adaptation analysis on the full-cycle business node data, and select the processing model type that matches the current business node from the preset scenario model library to generate scenario model matching data. S3. Perform business boundary delineation on the scene model matching data, and limit the processing range of each matching model by combining facility category, spatial range and business stage, and generate processing range limit data for each scene model; arrange the execution order of the processing range limit data of each scene model to generate scene model call priority sequence data. S4. Perform computational resource allocation processing on the priority sequence data of scene model calls, allocate independent running channels and data cache space to each scene model, and generate model resource pre-allocation data; prepare the model resource pre-allocation data for parallel operation and generate a multi-model parallel call ready signal; S5. Perform planning phase data loading processing on the running tasks corresponding to the multi-model parallel call ready signals, overlay and replay regional terrain data, road network planning data, and lighting brightness demand data to generate facility layout pre-simulation data; perform construction phase synchronization processing on the facility layout pre-simulation data to complete the real-time uploading of asset addition information, coordinate update information, and attribute change information during construction, and generate dynamic synchronization data of the construction process. S6. Perform joint processing of dynamic synchronous data during the construction process and operation and maintenance phases, and access real-time IoT monitoring data such as water level, leakage current, manhole cover status, and lighting rate to generate cross-facility joint early warning data; perform backtracking processing of cross-facility joint early warning data during the scrapping phase, complete the registration of spatial resource release after facility demolition, archive residual value information, and retain historical full-cycle data to generate full life cycle closed-loop archived data.

[0011] The working principle and effects of the above technical solution are as follows: By standardizing, spatiotemporally binding, and supplementing municipal facility ledger data, the data standards of various departments in the city can be unified, improving the completeness and regularity of basic municipal data and reducing business analysis biases caused by scattered and disorganized data. Through business node transformation and precise matching of scenario models, intelligent processing can be carried out in line with the entire lifecycle of facility business processes, enhancing the scenario adaptability of municipal facility management. Through model boundary constraints and priority arrangement, and pre-allocation of computing resources, parallel computing of multiple models can be carried out in an orderly manner, avoiding data conflicts and computational errors that occur when multiple tasks run simultaneously, and reducing system resource waste. Simultaneously, relying on a full-process control mode of GIS spatial simulation, construction dynamic synchronization, and IoT monitoring linkage and traceability, it can cover the entire lifecycle management of facilities from planning, construction, operation and maintenance to decommissioning, and can promptly capture facility operation anomalies and retain complete facility archives, effectively improving the overall management accuracy and closed-loop control capabilities of municipal facilities.

[0012] One embodiment of the present invention, such as Figure 2 As shown, S1 includes: S11. Collect original municipal facility ledger data pushed by multiple business channels of urban housing construction, urban management, water affairs and sanitation, uniformly convert data storage code and form storage structure, clear blank records, garbled characters, incomplete records and invalid data entries, remove duplicate entries of facilities with the same coordinates and numbers, and output neat and unified municipal basic source data. S12. Deconstruct and organize the built-in composite fields of the municipal basic source data, split the composite text of facility specifications, laying years and ownership units, classify all fields according to three dimensions: spatial attributes, business attributes and asset attributes, extract the identification text of facility type, location, latitude and longitude interval, construction, operation and maintenance and scrapping stage, and output a multi-level asset feature aggregated dataset. S13. Retrieve the underlying spatial calculation module of the unified GIS across the entire domain, read the internal coordinate identifiers of the multi-level asset feature aggregation dataset, use the grid anchoring matching algorithm to uniquely associate a single facility asset item with a geographic grid point, and output the intermediate data for binding the geographic coordinates of the facility entity. S14. Fill the intermediate data of the facility entity geographic coordinate binding to the preset phased life cycle data storage architecture one by one, divide the four independent storage partitions of planning, construction, operation and maintenance and disposal to carry the binding information, and output the asset spatiotemporal binding tag dataset with partition identifier; S15. Retrieve offline existing business data tables from each business department, compare the missing attribute fields of the asset spatiotemporal binding tag dataset with partition identifier, fill in the unsynchronized information of pipeline diameter, manhole cover load, street light power, facility maintenance records, and output a complete dimensional municipal asset mapping dataset.

[0013] The working principle and effects of the above technical solution are as follows: By standardizing, cleaning, and deduplicating the original ledger data of municipal facilities from multiple channels, the storage format of various business data can be unified, reducing the interference of invalid and duplicate data on subsequent business processing and significantly improving the overall quality of municipal basic data. By splitting standardized data into fields and extracting data through multi-dimensional classification, the various attribute characteristics of municipal facilities can be refined, allowing scattered facility data to form a standardized feature system, improving the precision of subsequent spatial matching and business analysis. By using GIS grid anchoring technology to establish a unique association between facility entities and geographical locations, accurate spatial positioning of municipal facilities can be achieved, eliminating problems such as disordered facility geographical information and matching deviations. Through phased data partitioning storage and cross-departmental data completion processing, missing facility attribute information in various business links can be supplemented, and the unified integration of municipal asset data across the entire domain can be achieved, effectively improving the completeness, uniformity, and usability of municipal facility basic data.

[0014] In one embodiment of the present invention, S13 includes: Read the core spatial and attribute fields inside the multi-level asset feature aggregation dataset, call the unified GIS underlying data parsing unit to decompose and reorganize the aggregated data in a structured manner, separate the mixed and merged spatial point information and asset attribute information, and generate regularized GIS structured field data; Model adaptation features are extracted from the structured field data of the regularized GIS, and core data elements that are adapted to spatial binding operations and asset association matching are selected to generate a GIS model adaptation feature dataset. The model library is traversed and compared on the GIS model adaptation feature dataset. The preset GIS spatial matching model cluster is called to complete the overlap comparison between feature elements and model adaptation parameters, filter out the model types that are suitable for the current data operation requirements, and generate preliminary GIS model matching data. The initial matching data of GIS models is subjected to fit verification and screening. Invalid matching models with feature fit below the unified standard are removed, and model entries with qualified fit are retained to generate accurate GIS model type matching data.

[0015] The working principle and effects of the above technical solution are as follows: By structurally decomposing and reorganizing aggregated asset feature data, mixed spatial information and asset attribute information can be completely separated, reducing data computation disorder caused by mixed fields and improving the regularity of GIS data processing. By selectively extracting core feature elements suitable for spatial binding and asset matching, invalid and redundant data content can be simplified, improving the overall speed of subsequent model calculations. By traversing the entire GIS spatial matching model cluster to complete feature comparison, suitable models can be selected according to current data computation needs, improving the fit of model matching. By standardizing the fitness verification, ineffective models that do not meet the standards are filtered out, avoiding resource consumption caused by inefficient models participating in the calculation. The entire processing method can not only ensure the accuracy of municipal facility spatial binding calculations, but also simplify the system's computational load, effectively improving the overall efficiency and stability of GIS facility spatial matching work.

[0016] In one embodiment of the present invention, step S14 includes: Read the intermediate data bound to the geographical coordinates of the facility entity, parse the facility category parameters, geographical coverage, and core elements of business affiliation stage carried by each data point, complete the multi-dimensional element decomposition and extraction, and generate aggregated data of facility boundary elements; The spatial and business dimensions of the aggregated data of facility boundary elements are calibrated to conform to the whole-domain GIS grid division specifications and the municipal facility full life cycle management standards, and the standardized constraint correction of the retrieval interval is completed to generate the original data of facility retrieval boundary. Perform full-domain interval comparison and detection on the raw data of facility retrieval boundaries, identify abnormal data with overlapping spatial ranges, overlapping business dimensions, and misaligned stage intervals, and complete unified correction to generate conflict-free standardized facility retrieval boundary data; The weight allocation rules of the four major storage partitions throughout the entire lifecycle are retrieved, and the boundary data of the conflict-free standardized facilities are sorted and normalized hierarchically. The business management priority of each partition is matched, and the partition boundary priority sequence data is generated. The priority sequence data of the partition boundary is synchronously entered into the preset phased lifecycle data storage architecture to complete the accurate adaptation and mounting of the boundary data with each independent storage partition, and output a dataset of asset spatiotemporal binding tags with partition identifiers.

[0017] The working principle and effects of the above technical solution are as follows: By extracting multi-dimensional core elements of facilities, the spatial and business attribute information of facilities can be fully sorted out, making boundary data extraction more detailed and comprehensive. By standardizing and calibrating the retrieval intervals, the interval specifications of all facility data can be unified, reducing deviations caused by different facility data management standards. Through full-domain interval comparison detection and anomaly correction, various problems such as data overlap, dimension intersection, and interval misalignment can be cleaned up, preventing data errors during subsequent data storage and retrieval. By combining partition weight rules to complete data hierarchical sorting, data priority can be divided according to the needs of facility full life cycle management, making data classification more in line with actual business scenarios. The entire processing method can not only ensure the standardization and independence of facility spatiotemporal data storage, but also improve the accuracy of life cycle data partitioning and mounting, effectively enhancing the orderliness of municipal facility full life cycle data management.

[0018] In one embodiment of the present invention, S2 includes: S21. Read the partitioned storage content of the complete municipal asset mapping dataset, break down the six independent business processes of planning, project establishment, construction, acceptance, daily inspection, fault repair, scrapping and disposal, convert the partitioned static asset records into lightweight standardized business node records that can be retrieved across processes, and output the full-cycle coherent business node dataset. S22. Traverse the full-cycle coherent business node dataset. Each node has built-in stage identifier, spatial range identifier, and facility type identifier. Retrieve the local storage of multiple municipal business scenario model libraries. Compare the overlap between node identifiers and model adaptation labels group by group. Output the preliminary scenario adaptation comparison results data. S23. Perform overlap weighting calculation on the preliminary scene adaptation comparison results data, remove unsuitable scene models with matching weights below the preset threshold, retain the model entries with matching weights that meet the standard, and output the accurate scene model matching result dataset.

[0019] The working principle and effects of the above technical solution are as follows: By breaking down various business processes throughout the entire lifecycle of municipal facilities and transforming them into standardized business node records, data barriers between different business links can be broken down, allowing static asset data to be flexibly accessed in different business scenarios, thus improving the reusability of municipal business data. By comparing the overlap between various identifiers of business nodes and scenario model adaptation tags, a comprehensive screening of suitable business processing models can be conducted, broadening the scope of model matching. By using weighted calculations to screen compliant model entries, invalid models with insufficient adaptability can be eliminated, reducing processing deviations caused by unqualified models participating in business operations. The entire processing method not only ensures a high degree of fit between business scenarios and processing models but also improves the overall accuracy of business processing throughout the entire lifecycle of municipal facilities, effectively reducing mismatches and omissions in business processing and continuously improving the operational efficiency of digital management of municipal facilities.

[0020] In one embodiment of the present invention, step S23 includes: Extract the original parameters of the overlap of each group of adaptation labels from the preliminary scene adaptation ratio results data, complete the superposition and integration calculation of multi-dimensional weight factors, and generate scene model comprehensive adaptation weight data; A full-domain threshold screening is performed on the scene model comprehensive adaptation weight data to remove scene model entries whose weight values ​​do not meet the unified screening standard, and preliminary adaptation model screening data is generated. Cross-business scenario conflict verification is performed on the preliminary model screening data to identify redundant model data with overlapping adaptation ranges and duplicate business processing dimensions, and deduplicated and optimized model adaptation data is generated. The deduplication and optimization model adaptation data is organized and categorized, the storage and arrangement format and parameter dimensions of the remaining model data are unified, and the accurate scene model matching result dataset is output.

[0021] The working principle and effects of the above technical solution are as follows: By performing multi-dimensional weighted calculations on model adaptation parameters, various matching indicators can be comprehensively considered, making the judgment result of model adaptation degree more objective and comprehensive, and improving the rationality of model selection. By filtering out substandard model data through full-domain threshold screening, invalid models with poor adaptation effects can be filtered out, reducing system resource consumption caused by inefficient calculations. By verifying and investigating model adaptation overlap and dimension duplication issues across business scenarios, various redundant model data can be cleaned up, avoiding business processing chaos caused by repeated calculations of multiple models. By standardizing the data format and parameter dimensions of the remaining models, the model data output standard can be unified, ensuring the smooth progress of subsequent business calculations. This entire processing method not only improves the accuracy of scenario model matching but also optimizes the overall calculation process, effectively reducing the probability of errors in municipal business scenario processing and ensuring the orderly operation of facility management business.

[0022] In one embodiment of the present invention, S3 includes: S31. Read the single model adaptation parameter of the accurate scene model matching result dataset, extract the three types of constraint factors of the business execution stage of the geographical area covered by the facility category corresponding to the model, define the independent data processing boundary interval for the single scene model, and output the original dataset of single model boundary constraints. S32. Merge all single-model boundary constraint original datasets and perform boundary overlap region detection. Perform interval cutting and splitting on model boundaries with spatial interval business time periods to eliminate data coverage conflicts in multi-model parallel operation and output a complete dataset with no overlapping model boundaries. S33. Read the complete dataset with non-overlapping model boundary constraints. Process the data volume indicators of the built-in business urgency coefficient of each model, arrange the order of model execution according to the comprehensive weight of the two indicators, and output the ordered scenario model call priority sequence dataset.

[0023] The working principle and effects of the above technical solution are as follows: By defining dedicated data processing boundary ranges for each scenario model, the processing scope of different business models can be distinguished, improving the targeting and standardization of single-model business operations. Through batch detection and segmentation of overlapping spaces and business ranges, the problems of data coverage and computational conflicts during parallel operation of multiple models can be resolved, reducing data corruption and result deviations during batch computation. By combining the urgency of business operations and the volume of data processing to arrange the model execution order, the system's computational resources can be rationally allocated, prioritizing the completion of core business processing tasks. This entire processing method not only ensures the stability of simultaneous operation of multiple models but also improves the efficiency and organization of overall business processing, avoiding common problems such as computational lag and data duplication caused by multi-task parallelism, making the intelligent processing flow of various scenarios in municipal facilities smoother and more reliable.

[0024] In one embodiment of the present invention, S32 includes: Integrate spatial interval parameters and business time period parameters from the original dataset of all single-model boundary constraints to complete the batch fusion and aggregation of multi-model boundary data and generate aggregated data of the entire model boundary. A full-domain comparison scan is performed on the aggregated boundary data of the full-domain model to identify various boundary conflict areas with overlapping spatial coverage, overlapping business time periods, and overlapping processing dimensions, and to generate statistical data on model boundary conflict points. The overlapping intervals corresponding to the statistical data of conflict points at the model boundary are finely segmented and split, and the independent processing intervals are split according to the facility business management dimension to generate boundary split correction data. Perform a global consistency check on the boundary split correction data, verify the independence and integrity of all model boundary intervals, avoid data omissions and interval deviations, and output a complete dataset with non-overlapping model boundary constraints.

[0025] The working principle and effects of the above technical solution are as follows: By batch merging and aggregating boundary data from multiple models, unified sorting of boundary information across the entire domain can be achieved, eliminating blind spots in management caused by scattered data processing. By scanning and screening various boundary conflict points across the entire domain, overlapping issues in space, time period, and business dimensions can be comprehensively captured, reducing the omission of conflicting data. By finely segmenting and splitting overlapping intervals, the processing intervals of each model can be made independent, preventing data interference problems that occur during parallel multi-model operations. By correcting interval deviations and data missing issues through global consistency verification, the integrity and standardization of all model boundary data can be guaranteed. This entire processing method not only improves the overall stability of multi-model collaborative operations but also makes data processing in various municipal business scenarios more accurate and standardized, effectively reducing the probability of batch operation errors and continuously improving the operational quality of scenario-based management of municipal facilities.

[0026] In one embodiment of the present invention, step S4 includes: S41. Read all the model entries to be run in the ordered scene model priority sequence dataset, divide the server computing power, memory and storage into three types of hardware resources, divide each sequence model into an independent computing power running channel and a dedicated temporary data cache partition, and output the model hardware resource pre-division dataset. S42. Detect the occupancy status of the pre-partitioned dataset allocation channel cache partition of the hardware resources of the detection model, clean up idle cache fragments in the background of the server to release redundant memory space, complete the empty verification of the allocated resource channel, and output the pre-allocated dataset after resource verification is completed. S43. Issue model start-up pre-verification instructions to each independent computing power operation channel, and sequentially complete scene model file integrity verification, input data channel connectivity verification, cache read / write permission verification. After all verification items pass, generate a multi-model synchronous running ready status identifier data stream.

[0027] The working principle and effects of the above technical solution are as follows: By allocating dedicated computing power channels and cache partitions according to the model running order, the computing processes of different models can be separated, reducing computing lag caused by multiple tasks competing for hardware resources. By clearing cache fragments, releasing idle memory, and verifying the channel's idle status, idle hardware space can be reclaimed, reducing the server load caused by invalid resource occupation. By checking the three types of operating conditions—model files, data channels, and read / write permissions—layer by layer, various startup failures can be detected in advance, avoiding business process stagnation caused by model interruptions. The entire processing method can not only evenly allocate server hardware resources but also remove various obstacles to the parallel operation of multiple models in advance, effectively improving the success rate of starting batch municipal business models, reducing resource waste and abnormal program interruptions, and ensuring the stable and smooth batch computing process of full-cycle facility management.

[0028] In one embodiment of the present invention, step S5 includes: S51. Receive the multi-model synchronous running ready status flag data stream to start the batch data loading process, retrieve the full-domain GIS topography elevation vector layer, urban road network vector layer, municipal lighting load demand layer, complete the pixel-level overlay rendering calculation of the three vector layers, and output the complete dataset of municipal facility early layout simulation. S52. Real-time collection of basic information of all newly added pipeline, street light and manhole cover facilities from mobile terminals at the construction site, synchronous capture of facility geographic coordinate offset data after updating and correcting the construction surveying equipment, and output of original data stream of construction additions and changes. S53. Write the original data stream of new construction changes into the corresponding facility partition layer of the GIS base in real time, refresh the facility specification, ownership and construction progress attribute fields in the layer synchronously, continuously retain the change records of the entire construction period, and output the dynamic time-series synchronized dataset of the construction phase.

[0029] The working principle and effects of the above technical solution are as follows: By overlaying and rendering multiple GIS vector layers at the pixel level to simulate facility layout, the interaction between terrain, road network, and lighting requirements can be intuitively presented, improving the detail of early-stage facility layout prediction. By synchronously collecting information on newly added facilities and coordinate corrections uploaded from multiple terminals at the construction site, various changes during the construction phase can be fully captured, reducing data lag issues caused by manual offline reporting. By writing construction change data to the GIS layer in real time and continuously retaining time-series records, all facility attribute content can be updated synchronously, eliminating the problem of discrepancies between drawing information and actual site conditions. This entire processing method can reduce the later modification costs caused by unreasonable facility layout during the planning phase, and can retain a complete construction change trajectory throughout the process, effectively improving the predictive ability of municipal facility planning and the real-time and completeness of data updates during the construction phase.

[0030] In one embodiment of the present invention, step S6 includes: S61. Connect to the urban underground pipe network water level sensor cable leakage current monitoring terminal, manhole cover attitude sensing equipment, road lighting brightness acquisition terminal to transmit continuous monitoring values ​​in real time, associate and mount the single facility monitoring values ​​with the corresponding facility points in the GIS layer, and output the original data stream of synchronous monitoring of multiple municipal facilities. S62. Read the built-in real-time values ​​of the original data stream of synchronous monitoring of multiple municipal facilities, compare them with the preset safe operation value range of each type of facility, identify abnormal monitoring items that exceed the safe range, and generate a cross-facility linkage abnormal early warning dataset by associating it with similar facilities such as pipelines, lights, and manhole covers in the same area. S63. Read the full-cycle time-series records of a single facility stored in the cross-facility linkage anomaly early warning dataset, filter and mark the facility entities that have completed the demolition and disposal process, release the geographical grid point resources occupied by the facility in the GIS layer, register the residual value calculation value of facility demolition, and output the intermediate archive data of scrapping and disposal. S64. Merge the intermediate archived data of the scrapping and disposal with the time-series data of the facility's planning, construction and operation and maintenance throughout the entire period and store it in the underlying historical archive partition of the GIS. Lock the archive partition data with read-only permission to prevent tampering, and output a complete closed-loop archived dataset of the single facility's entire life cycle.

[0031] The working principle and effects of the above technical solution are as follows: By transmitting data back from various on-site monitoring terminals and binding them to GIS facility locations, the operational status of multiple types of facilities can be collected simultaneously, improving the completeness of capturing the operational status of facilities across the entire area. By comparing real-time monitoring values ​​with safe zones to identify anomalies, early warning content is generated in conjunction with similar facilities in the area, reducing large-scale facility losses caused by the omission of single equipment failures. By releasing geographic grids and registering residual values ​​for decommissioned facilities, space resources can be freed up in a timely manner, avoiding the problem of spatial statistical distortion caused by long-term occupation of layers by abandoned facilities. By integrating the time-series data of facilities at each stage into read-only archive partitions, all historical records can be completely preserved, preventing the loss of original management data due to human intervention. The entire processing method can not only detect potential facility operation hazards early and reduce fault repair costs, but also form an unalterable and complete facility archive, effectively completing the closed-loop management of municipal facilities from operation monitoring to decommissioning and retention.

[0032] One embodiment of the present invention provides a GIS-based municipal infrastructure lifecycle management system, the system comprising: One or more processors; Memory, used to store one or more programs; Wherein, when the one or more programs are executed by the one or more processors, the one or more processors are made to implement the method described in any one of the above.

[0033] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A GIS-based method for the full lifecycle management of municipal facilities, characterized in that, The method includes: S1. Perform field splitting and attribute classification on the standardized municipal infrastructure basic data to generate a multi-dimensional asset feature set; perform spatiotemporal correlation matching on the multi-dimensional asset feature set to generate asset spatiotemporal binding tag data; perform cross-departmental data completion on the asset spatiotemporal binding tag data to generate full-attribute asset mapping data. S2. Perform business flow transformation processing on the full-attribute asset mapping data to generate full-cycle business node data; perform scenario adaptation analysis on the full-cycle business node data, select the processing model type that matches the current business node from the preset scenario model library, and generate scenario model matching data. S3. Perform business boundary delineation on the scene model matching data, and limit the processing range of each matching model by combining facility category, spatial range and business stage, and generate processing range limit data for each scene model; arrange the execution order of the processing range limit data of each scene model to generate scene model call priority sequence data. S4. Perform computational resource allocation processing on the priority sequence data of scene model calls, allocate independent running channels and data cache space to each scene model, and generate model resource pre-allocation data; prepare the model resource pre-allocation data for parallel operation and generate a multi-model parallel call ready signal; S5. Perform planning phase data loading processing on the running tasks corresponding to the multi-model parallel call ready signals to generate facility deployment pre-simulation data; perform construction phase synchronization processing on the facility deployment pre-simulation data to generate dynamic synchronization data of the construction process. S6. Perform joint processing on the dynamic synchronous data during the construction process and maintenance phase to generate cross-facility joint early warning data; perform backtracking processing on the cross-facility joint early warning data during the scrapping phase to generate closed-loop archived data throughout the entire life cycle.

2. The GIS-based full lifecycle management method for municipal facilities according to claim 1, characterized in that, S1 includes: S11. Collect original municipal facility ledger data pushed by multiple business channels of urban housing construction, urban management, water affairs and sanitation, uniformly convert data storage code and form storage structure, clear blank records, garbled characters, incomplete records and invalid data entries, remove duplicate entries of facilities with the same coordinates and numbers, and output neat and unified municipal basic source data. S12. Deconstruct and organize the built-in composite fields of the municipal basic source data, split the composite text of facility specifications, laying years and ownership units, classify all fields according to three dimensions: spatial attributes, business attributes and asset attributes, extract the identification text of facility type, location, latitude and longitude interval, construction, operation and maintenance and scrapping stage, and output a multi-level asset feature aggregated dataset. S13. Retrieve the underlying spatial calculation module of the unified GIS across the entire domain, read the internal coordinate identifiers of the multi-level asset feature aggregation dataset, use the grid anchoring matching algorithm to uniquely associate a single facility asset item with a geographic grid point, and output the intermediate data for binding the geographic coordinates of the facility entity. S14. Fill the intermediate data of the facility entity geographic coordinate binding to the preset phased life cycle data storage architecture one by one, divide the four independent storage partitions of planning, construction, operation and maintenance and disposal to carry the binding information, and output the asset spatiotemporal binding tag dataset with partition identifier; S15. Retrieve offline existing business data tables from each business department, compare the missing attribute fields of the asset spatiotemporal binding tag dataset with partition identifier, fill in the unsynchronized information of pipeline diameter, manhole cover load, street light power, facility maintenance records, and output a complete dimensional municipal asset mapping dataset.

3. The GIS-based full lifecycle management method for municipal facilities according to claim 2, characterized in that, S13 includes: Read the core spatial and attribute fields inside the multi-level asset feature aggregation dataset, call the unified GIS underlying data parsing unit to decompose and reorganize the aggregated data in a structured manner, separate the mixed and merged spatial point information and asset attribute information, and generate regularized GIS structured field data; Model adaptation features are extracted from the structured field data of the regularized GIS, and core data elements that are adapted to spatial binding operations and asset association matching are selected to generate a GIS model adaptation feature dataset. The model library is traversed and compared on the GIS model adaptation feature dataset. The preset GIS spatial matching model cluster is called to complete the overlap comparison between feature elements and model adaptation parameters, filter out the model types that are suitable for the current data operation requirements, and generate preliminary GIS model matching data. The initial matching data of GIS models is subjected to fit verification and screening. Invalid matching models with feature fit below the unified standard are removed, and model entries with qualified fit are retained to generate accurate GIS model type matching data.

4. The GIS-based full lifecycle management method for municipal facilities according to claim 1, characterized in that, S2 includes: S21. Read the partitioned storage content of the complete municipal asset mapping dataset, break down the six independent business processes of planning, project establishment, construction, acceptance, daily inspection, fault repair, scrapping and disposal, convert the partitioned static asset records into lightweight standardized business node records that can be retrieved across processes, and output the full-cycle coherent business node dataset. S22. Traverse the full-cycle coherent business node dataset. Each node has built-in stage identifier, spatial range identifier, and facility type identifier. Retrieve the local storage of multiple municipal business scenario model libraries. Compare the overlap between node identifiers and model adaptation labels group by group. Output the preliminary scenario adaptation comparison results data. S23. Perform overlap weighting calculation on the preliminary scene adaptation comparison results data, remove unsuitable scene models with matching weights below the preset threshold, retain the model entries with matching weights that meet the standard, and output the accurate scene model matching result dataset.

5. The GIS-based full life-cycle management method for municipal facilities according to claim 1, characterized in that, The S3 includes: S31. Read the single model adaptation parameter of the accurate scene model matching result dataset, extract the three types of constraint factors of the business execution stage of the geographical area covered by the facility category corresponding to the model, define the independent data processing boundary interval for the single scene model, and output the original dataset of single model boundary constraints. S32. Merge all single-model boundary constraint original datasets and perform boundary overlap region detection. Perform interval cutting and splitting on model boundaries that have spatial interval business time periods that overlap, and output a complete dataset with no overlapping model boundaries. S33. Read the complete dataset with non-overlapping model boundary constraints. Process the data volume indicators of the built-in business urgency coefficient of each model, arrange the order of model execution according to the comprehensive weight of the two indicators, and output the ordered scenario model call priority sequence dataset.

6. The GIS-based full life-cycle management method for municipal facilities according to claim 5, characterized in that, S32 includes: Integrate spatial interval parameters and business time period parameters from the original dataset of all single-model boundary constraints to complete the batch fusion and aggregation of multi-model boundary data and generate aggregated data of the entire model boundary. A full-domain comparison scan is performed on the aggregated boundary data of the full-domain model to identify various boundary conflict areas with overlapping spatial coverage, overlapping business time periods, and overlapping processing dimensions, and to generate statistical data on model boundary conflict points. The overlapping intervals corresponding to the statistical data of conflict points at the model boundary are finely segmented and split, and the independent processing intervals are split according to the facility business management dimension to generate boundary split correction data. Perform a global consistency check on the boundary split correction data, verify the independence and integrity of all model boundary intervals, avoid data omissions and interval deviations, and output a complete dataset with non-overlapping model boundary constraints.

7. The GIS-based full life-cycle management method for municipal facilities according to claim 1, characterized in that, The S4 includes: S41. Read all the model entries to be run in the ordered scene model priority sequence dataset, divide the server computing power, memory and storage into three types of hardware resources, divide each sequence model into an independent computing power running channel and a dedicated temporary data cache partition, and output the model hardware resource pre-division dataset. S42. Detect the occupancy status of the pre-partitioned dataset allocation channel cache partition of the hardware resources of the detection model, clean up idle cache fragments in the background of the server to release redundant memory space, complete the empty verification of the allocated resource channel, and output the pre-allocated dataset after resource verification is completed. S43. Issue model start-up pre-verification instructions to each independent computing power operation channel, and sequentially complete scene model file integrity verification, input data channel connectivity verification, cache read / write permission verification. After all verification items pass, generate a multi-model synchronous running ready status identifier data stream.

8. The GIS-based full life-cycle management method for municipal facilities according to claim 1, characterized in that, The S5 includes: S51. Receive the multi-model synchronous running ready status flag data stream to start the batch data loading process, retrieve the full-domain GIS topography elevation vector layer, urban road network vector layer, municipal lighting load demand layer, complete the pixel-level overlay rendering calculation of the three vector layers, and output the complete dataset of municipal facility early layout simulation. S52. Real-time collection of basic information of all newly added pipeline, street light and manhole cover facilities from mobile terminals at the construction site, synchronous capture of facility geographic coordinate offset data after updating and correcting the construction surveying equipment, and output of original data stream of construction additions and changes. S53. Write the original data stream of new construction changes into the corresponding facility partition layer of the GIS base in real time, refresh the facility specification, ownership and construction progress attribute fields in the layer synchronously, continuously retain the change records of the entire construction period, and output the dynamic time-series synchronized dataset of the construction phase.

9. The GIS-based full life-cycle management method for municipal facilities according to claim 1, characterized in that, The S6 includes: S61. Connect to the urban underground pipe network water level sensor cable leakage current monitoring terminal, manhole cover attitude sensing equipment, road lighting brightness acquisition terminal to transmit continuous monitoring values ​​in real time, associate and mount the single facility monitoring values ​​with the corresponding facility points in the GIS layer, and output the original data stream of synchronous monitoring of multiple municipal facilities. S62. Read the built-in real-time values ​​of the original data stream of synchronous monitoring of multiple municipal facilities, compare them with the preset safe operation value range of each type of facility, identify abnormal monitoring items that exceed the safe range, and generate a cross-facility linkage abnormal early warning dataset by associating it with similar facilities such as pipelines, lights, and manhole covers in the same area. S63. Read the full-cycle time-series records of a single facility stored in the cross-facility linkage anomaly early warning dataset, filter and mark the facility entities that have completed the demolition and disposal process, release the geographical grid point resources occupied by the facility in the GIS layer, register the residual value calculation value of facility demolition, and output the intermediate archive data of scrapping and disposal. S64. Merge the intermediate archived data of the scrapping and disposal with the time-series data of the facility's planning, construction and operation and maintenance throughout the entire period and store it in the underlying historical archive partition of the GIS. Lock the archive partition data with read-only permission to prevent tampering, and output a complete closed-loop archived dataset of the single facility's entire life cycle.

10. A GIS-based municipal facilities lifecycle management system, characterized in that, The system includes: One or more processors; Memory, used to store one or more programs; Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 9.

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