A city management event intelligent dispatching method and system based on space-time dynamic responsibility adaptation, a terminal and a storage medium

Abstract

The application relates to the technical field of data processing, and discloses a city management event intelligent dispatching method and system based on space-time dynamic right and responsibility adaptation, a terminal and a storage medium.The method comprises the following steps: receiving standardized original work orders reported through multiple channels, extracting core feature data required for dispatching calculation from the original work orders after completing compliance verification and de-duplication filtering, generating a dynamic polygon area, then constructing a double-weight factor by using a double-layer right and responsibility rule engine, combining a multi-dimensional evaluation factor to perform normalization processing, finally obtaining a dispatching score of each candidate area, and adaptively dispatching the user according to the dispatching score.The application retains a stable multi-factor score basic logic, simultaneously introduces a space-time weight mechanism, realizes intelligent dispatching of city management event data driving, space-time adaptation, AI decision-making and dynamic optimization, and improves the dispatching accuracy and the dispatching efficiency.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to an intelligent dispatching method, system, terminal, and computer-readable storage medium for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation. Background Technology

[0002] With the continuous advancement of smart city construction, the urban grid management model has been widely adopted. Citizens can report various urban management incidents, such as facility damage and safety hazards, through multiple channels including apps, hotlines, and mini-programs. Urban management incidents are characterized by a large volume of reports, complex scenarios, geographical dispersion, overlapping responsibilities, and varying degrees of urgency, placing extremely high demands on the timeliness and accuracy of incident acceptance, classification, dispatch, and handling.

[0003] However, the existing scheduling system adopts a static operation mode of fixed rule matching and manual correction. The system only mechanically dispatches orders based on the event type, fixed grid area and preset list of rights and responsibilities filled in by the user, and does not have dynamic scheduling capabilities.

[0004] However, for complex events involving overlapping responsibilities, multi-regional co-management, and varying degrees of urgency, there is still a high reliance on manual secondary verification, reassignment, and adjustment by the command center. The overall level of intelligent dispatch is low and cannot meet the needs of modern urban governance and dispatch for massive emergencies and diverse scenarios.

[0005] Therefore, existing technologies still need to be improved and developed. Summary of the Invention

[0006] The main objective of this invention is to provide an intelligent dispatching method, system, terminal, and computer-readable storage medium for urban management events based on spatiotemporal dynamic responsibility adaptation, aiming to solve the problems of low dispatching efficiency and weak adaptability caused by the fixed scheduling mode of static rule matching and the manual judgment mode in the prior art.

[0007] To achieve the above objectives, the present invention provides an intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation. The intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation includes the following steps: The system acquires user-inputted reported events, constructs standardized work orders based on these events, inputs the standardized work orders into a pre-constructed information extraction model for compliance verification, and outputs time location information and event attribute information. The time and location information is input into the GIS fence engine for analysis, and the dynamic polygonal area of ​​the reported event is output. The event attribute information is input into the rule table engine for analysis, and the dual responsibility factor is output. A distance factor is constructed based on the dynamic polygon region, a load factor and a historical performance factor are constructed based on the business data input by the user, and multiple weight matching coefficients are determined based on the event attribute information. Based on all the weight matching coefficients, a comprehensive score for each candidate region is calculated based on the dual responsibility factor, the distance factor, the load factor and the historical performance factor. The target region is selected from all the candidate regions based on the comprehensive scores, and a dispatch instruction is constructed based on the time location information and event attribute information. The dispatch instruction is then sent to the target region for dispatching.

[0008] Optionally, the intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation, wherein the steps of obtaining the reported event input by the user, constructing a standardized work order based on the reported event, inputting the standardized work order into the constructed information extraction model for compliance verification, and outputting time and location information and event attribute information, specifically include: Obtain the reported events input by the user, and construct an original work order based on all the reported events. The original work order includes latitude and longitude, secondary category of the event, reporting time and event description information. The latitude and longitude, the secondary category of the event, and the reporting time are verified for completeness. The event description information is completed by field completion. Based on the completed latitude and longitude and time, it is determined whether the reported event is a valid work order. If it is a valid work order, then the secondary category of the reported event is matched. If the match fails, it is returned to the primary category for reassignment until a match is successful, and the event type of the reported event is obtained. Based on the verification latitude and longitude, the time, and the event type, determine whether the reported event is a duplicate work order; if not, construct a standardized work order for the reported event. The standardized work order is input into the information extraction model for information classification, and the time and location information and event attribute information of the reported event are output.

[0009] Optionally, the intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation, wherein the step of inputting the time and location information into a GIS fence engine for analysis and outputting the dynamic polygonal area of ​​the reported event, and inputting the event attribute information into a rule table engine for analysis and outputting dual responsibility factors, specifically includes: The verification latitude and longitude and the time are input into the GIS fence engine for analysis; If the time is a regular period, the regular jurisdiction area where the reported event is located is determined based on the verified latitude and longitude. If the time is an irregular time, the dynamic polygon area where the verified latitude and longitude is located during the time period is determined based on the special activity information in the GIS geographic information database, and the regular jurisdiction area or the dynamic polygon area is output. The regular jurisdiction area, the event type, and the urgency level are input into the rule table engine. The rule table engine performs responsibility analysis on the time and outputs the dual responsibility factor.

[0010] Optionally, the intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities includes, wherein the dual rights and responsibilities factors include: a responsibility matching factor and a spatiotemporal responsibility factor. The process of inputting the regular jurisdiction area, the event type, and the urgency level into the rule table engine, performing responsibility analysis on the time based on the rule table engine, and outputting the dual responsibility factor specifically includes: If the time period is a regular time period, the rule table engine constructs an inherent static responsibility rule table based on the responsibility matching list in the GIS geographic information database, and determines the responsibility matching factor of the reported event from the inherent static responsibility rule table according to the regular jurisdiction area and the event type, and outputs it; If the time is an unusual time, the rule table engine constructs a spatiotemporal temporary responsibility rule table based on the special activity information, determines the spatiotemporal responsibility factor of the reported event from the spatiotemporal temporary responsibility rule table based on the dynamic polygon region, the event type, and the urgency level, and outputs it.

[0011] Optionally, the intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation, wherein constructing a distance factor based on the dynamic polygonal region and constructing a load factor and historical performance factor based on user-input business data specifically includes: Construct a distance factor based on the dynamic polygon region: ; in, Represents the distance factor. This represents the path between the candidate region and the verification latitude and longitude coordinates. This represents the farthest path from the check latitude and longitude coordinates within the candidate region set. For each candidate region, obtain the business data of the candidate region, calculate the equivalent load value of the candidate region based on the current number of valid pending work orders and the number of completed work orders for the day in the business data, and construct a load factor based on the equivalent load value: ; in, Indicates the equivalent load value. This indicates the number of currently active work orders. Indicates the fatigue coefficient. This indicates the number of work orders completed that day; ; in, Indicates the load factor. This indicates the preset maximum load threshold; For each candidate region, all historical closed work orders within a preset time period are obtained, and the processing data of the same secondary category events as each historical closed work order are statistically analyzed to obtain the average processing time, first-time completion rate, user satisfaction rate, and rework / redispatch rate. Calculate the timeliness score based on the average processing time and the longest average processing time in the candidate region set: ; in, Indicates the timeliness score. Indicates the average processing time. Indicates the longest average processing time; Calculate the quality score of the candidate region based on the first-time completion rate, the user satisfaction rate, and the rework / redispatch rate: ; in, Indicates the quality score. This indicates the one-time completion rate. Indicates user satisfaction rate. Indicates the rework and reassignment rate; The timeliness score and the quality score are weighted and fused to obtain the historical performance factor of the candidate region: ; in, This represents the historical performance factor.

[0012] Optionally, the intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation, wherein determining multiple weight matching coefficients based on the event attribute information, and calculating a comprehensive score for each candidate area based on all the weight matching coefficients, according to the dual rights and responsibilities factor, the distance factor, the load factor, and the historical performance factor, specifically includes: Obtain a preset weight configuration table, and determine multiple weight matching coefficients from the weight configuration table according to the event type and urgency. The dual-responsibility factor, the distance factor, the load factor, and the historical performance factor are weighted according to all the weight matching coefficients to calculate the comprehensive score of each candidate region: ; in, This indicates the overall score. Represents the distance factor. express The weighted matching coefficient, Indicates the load factor. express The weighted matching coefficient, Indicates the responsibility matching factor. express The weighted matching coefficient, Represents historical performance factor. express The weighted matching coefficient, Indicates the spatiotemporal responsibility factor. express The weighted matching coefficient.

[0013] Optionally, the intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation, wherein the step of selecting a target area from all candidate areas based on all the comprehensive scores, constructing a dispatching instruction based on the time location information and event attribute information, and sending the dispatching instruction to the target area for dispatching specifically includes: Sort all the comprehensive scores to obtain a candidate region sorting list; The first preliminary selection area is selected from the candidate area sorting list, and a dispatch instruction is constructed based on the time location information and event attribute information. The dispatch instruction is then sent to the preliminary selection area. If the initial selection area does not receive the dispatch instruction, the dispatch instruction is sent to the second initial selection area ranked second, until a candidate area receives the dispatch instruction, then the candidate area is defined as the target. If none of the candidate regions in the candidate region sorting list have received the dispatch instruction, the dispatch instruction will be forwarded to the administrator for manual dispatch.

[0014] Furthermore, to achieve the above objectives, the present invention also provides an intelligent dispatch system for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation, wherein the intelligent dispatch system for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation includes: The information reporting module is used to obtain the reporting events input by the user, construct a standardized work order based on the reporting events, input the standardized work order into the constructed information extraction model for compliance verification, and output time location information and event attribute information. The factor analysis module is used to input the time and location information into the GIS fence engine for analysis, output the dynamic polygon area of ​​the reported event, input the event attribute information into the rule table engine for analysis, and output the dual responsibility factor. The weight matching and scoring module is used to construct a distance factor based on the dynamic polygon region, construct a load factor and a historical performance factor based on the business data input by the user, determine multiple weight matching coefficients based on the event attribute information, and calculate a comprehensive score for each candidate region based on all the weight matching coefficients, the dual responsibility factor, the distance factor, the load factor and the historical performance factor. The dispatch module is used to filter out the target area from all the candidate areas based on all the comprehensive scores, construct the dispatch instruction based on the time location information and event attribute information, and send the dispatch instruction to the target area for dispatching.

[0015] In addition, to achieve the above objectives, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and an intelligent dispatching program for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation stored in the memory and executable on the processor. When the intelligent dispatching program for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation is executed by the processor, it implements the steps of the intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation as described above.

[0016] Furthermore, to achieve the above objectives, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores an intelligent dispatching program for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation, and when the intelligent dispatching program for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation is executed by a processor, it implements the steps of the intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation as described above.

[0017] In this invention, user-inputted reported events are acquired; standardized work orders are constructed based on the reported events; these standardized work orders are input into a pre-constructed information extraction model for compliance verification, outputting time and location information and event attribute information; the time and location information is input into a GIS fence engine for analysis, outputting a dynamic polygonal region of the reported event; the event attribute information is input into a rule table engine for analysis, outputting a dual-responsibility factor; a distance factor is constructed based on the dynamic polygonal region; a load factor and a historical performance factor are constructed based on user-inputted business data; multiple weight matching coefficients are determined based on the event attribute information; based on all the weight matching coefficients, a comprehensive score for each candidate region is calculated according to the dual-responsibility factor, the distance factor, the load factor, and the historical performance factor; a target region is selected from all the candidate regions based on all the comprehensive scores; a dispatch instruction is constructed based on the time and location information and the event attribute information; and the dispatch instruction is sent to the target region for dispatching. This invention retains the stable multi-factor scoring logic while introducing a lightweight machine learning intelligent decision-making and spatiotemporal weighting mechanism to achieve intelligent dispatching driven by urban management event data, spatiotemporal adaptation, AI decision-making, and dynamic optimization, thereby improving dispatching accuracy and efficiency. Attached Figure Description

[0018] Figure 1 This is a flowchart of a preferred embodiment of the intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation of the present invention; Figure 2 This is a flowchart of a preferred embodiment of the intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation of the present invention. Figure 3 This is a structural diagram of a preferred embodiment of the intelligent dispatching system for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation of the present invention; Figure 4 This is a structural diagram of a preferred embodiment of the terminal of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] The preferred embodiment of the present invention describes an intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation, such as... Figure 1 As shown, the intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities includes the following steps: Step S10: Obtain the reported event input by the user, construct a standardized work order based on the reported event, input the standardized work order into the constructed information extraction model for compliance verification, and output time location information and event attribute information.

[0021] Among them, for reported events reported through multiple channels, an original work order can be constructed based on the various reported information. The system needs to perform compliance verification and deduplication filtering on the original work order, and then extract the core feature data required for dispatch calculation. Specifically, this includes: latitude and longitude verification of the incident location, reporting timestamp, secondary classification of the event, event urgency level, and unique work order number, providing standardized input for subsequent GIS (Geographic Information System) fence matching, authority and responsibility rule matching, and multi-factor scoring. Business details such as the reporter information and on-site supporting materials in the original work order do not participate in the dispatch calculation, but are only associated and retained through the work order number.

[0022] Specifically, the system obtains the reported events input by the user, constructs an original work order based on all the reported events, and the original work order includes latitude and longitude, secondary event category, reporting time, and event description information; The latitude and longitude, the secondary category of the event, and the reporting time are verified for completeness. The event description information is completed by field completion. Based on the completed latitude and longitude and time, it is determined whether the reported event is a valid work order. If it is a valid work order, then the secondary category of the reported event is matched. If the match fails, it is returned to the primary category for reassignment until a match is successful, and the event type of the reported event is obtained. Based on the verification latitude and longitude, the time, and the event type, determine whether the reported event is a duplicate work order; if not, construct a standardized work order for the reported event. The standardized work order is input into the information extraction model for information classification, and the time and location information and event attribute information of the reported event are output.

[0023] In this invention, a layered, progressive verification mechanism is employed when performing compliance checks on original work orders. Abnormal data is intercepted layer by layer, ensuring the legality and validity of the input data. Specifically, the completeness and format compliance of three core mandatory fields—latitude and longitude, event secondary category, and reporting time—are verified. Work orders with missing core fields or invalid formats are deemed invalid and directly archived. Missing supplementary fields, such as on-site attachments, do not hinder subsequent processes. This invention, through its layered, progressive verification architecture, breaks down complex compliance checks into independent levels, enabling precise interception of abnormal data at each level. This design significantly reduces system coupling, making the responsibilities of each verification stage clear and logically isolated, improving processing efficiency and facilitating subsequent maintenance and expansion. By differentiating verification strategies for core and supplementary fields, data quality is ensured while maintaining process flexibility, preventing the overall business flow from being blocked due to the lack of non-critical information.

[0024] Furthermore, for spatiotemporal compliance verification, it is determined whether the latitude and longitude fall within the service area vector boundary, eliminating null values ​​and obvious outliers. For work orders with slight deviations but containing valid address text, geocoding reverse correction is performed. In the time dimension, the reporting time logic is verified for rationality, and invalid work orders with future times or excessively long-term reports are eliminated. By introducing spatial vector boundary determination and time logic checks, a multi-dimensional data quality inspection system is constructed. The latitude and longitude verification combined with the geocoding reverse correction mechanism can both eliminate invalid latitude and longitude and intelligently correct slightly offset data, improving the usability of location data. The strict screening of the reporting logic in the time dimension effectively filters out abnormal work orders with future times or excessively long-term reports, ensuring the authenticity and compliance of input data from both spatiotemporal dimensions.

[0025] Finally, the event categories are matched with the responsibility category database. Successful matches at the secondary category level proceed normally; failures at the secondary category level result in matching at the primary category level, marked as pending confirmation, and then released; unknown work orders where all categories fail to match are transferred to a manual review queue, blocking the automatic dispatch process; invalid work orders with non-compliant content or no substantial event information are rejected. By establishing an intelligent matching mechanism between event categories and the responsibility system, hierarchical fault tolerance and differentiated processing are achieved. Accurate matching at the secondary category level ensures efficient operation of normal business processes, while automatic upward compatibility with the primary category and marking pending confirmation when a match fails demonstrates the system's robustness and flexibility. The design of transferring completely unknown categories to manual review and directly rejecting invalid work orders not only safeguards the bottom line of business operations but also focuses manual intervention on truly critical abnormal scenarios, optimizing human-machine collaboration efficiency. The invention features a differentiated spatial tolerance design that dynamically adjusts the buffer radius according to event type, balancing spatial accuracy and recall. The time window is flexibly set according to urgency level to adapt to the timeliness characteristics of different events. This dual screening method narrows the candidate set layer by layer, effectively reducing the computational overhead of subsequent semantic matching. While ensuring recognition accuracy, it significantly improves system processing performance and avoids resource waste caused by multiple channels reporting the same event.

[0026] Furthermore, for standardized work orders that have passed verification, a triple-progressive mechanism of spatial clustering, temporal sliding window, and semantic matching is used to identify duplicate work orders, avoiding duplicate reporting of the same event through multiple channels, which leads to duplicate dispatch and wasted resources. Specifically, firstly, differentiated spatial tolerance thresholds are set according to event type, such as a radius of 50 meters for point-like facility events, a radius of 100 meters for area-like urban appearance events, and a radius of 300 meters for large-scale public events. Unresolved work orders within the corresponding buffer are retrieved to form a spatial candidate set. Then, matching time windows are set according to the urgency level of the event, such as 1 hour for general events, 30 minutes for emergency events, and 24 hours for long-term events. Work orders within the same spatial and temporal range are filtered from the spatial candidate set to narrow down the precise matching range.

[0027] Furthermore, based on the secondary classification of events and the event description text, a feature fingerprint is constructed, and text similarity is calculated (if the similarity is greater than 85%, it is judged as a duplicate work order; if the similarity is between 60% and 85%, it is judged as a suspected duplicate). For duplicate work orders, the earliest generated work order is retained as the master work order, and the attachments and supplementary descriptions uploaded by the duplicate work order are automatically synchronized to the master work order as supporting materials, without generating an independent work order assignment task; suspected duplicate work orders are pushed for manual review and confirmation. By constructing a two-dimensional feature fingerprint of "classification + text", intelligent identification and flexible processing of duplicate work orders are achieved. Among them, the hierarchical design of similarity thresholds takes into account both accuracy and fault tolerance: high thresholds accurately intercept explicit duplicates and avoid resource waste; medium thresholds trigger manual review, retaining the space for manual judgment and reducing the risk of misjudgment; and for confirmed duplicate work orders, an automatic attachment merging strategy is adopted, which not only preserves the integrity of supporting information but also avoids resource redundancy caused by duplicate work order assignment, significantly improving work order processing efficiency and data consistency.

[0028] Finally, as Figure 2 As shown, based on the standardized work orders that have been verified, the information extraction model can be used to extract five core features: the latitude and longitude of the incident location, the reporting timestamp, the secondary category of the event, the urgency level of the event, and the unique work order number, which are then output to the subsequent GIS fence engine and rule table engine.

[0029] Step S20: Input the time and location information into the GIS fence engine for analysis, output the dynamic polygonal area of ​​the reported event, input the event attribute information into the rule table engine for analysis, and output the dual responsibility factor.

[0030] Specifically, the GIS fence engine is used to analyze the latitude and longitude of the incident site and the reporting timestamp to obtain dynamic polygonal areas in different time periods and regions. This breaks through the spatial limitations of traditional fixed fences and enables automatic access for cross-regional support forces in temporary scenarios. Then, combined with the rule table engine, long-term statutory functions are decoupled from short-term temporary permissions. Without the need for manual modification of basic rights and responsibilities configuration, it automatically adapts to the transfer of functions and support scheduling in special scenarios such as holidays, large-scale events, and temporary controls, filling the scenario gap of traditional fixed rights and responsibilities scheduling.

[0031] Specifically, the verification latitude and longitude and the time are input into the GIS fence engine for analysis; If the time is a regular period, the regular jurisdiction area where the reported event is located is determined based on the verified latitude and longitude. If the time is an irregular time, the dynamic polygon area where the verified latitude and longitude is located during the time period is determined based on the special activity information in the GIS geographic information database, and the regular jurisdiction area or the dynamic polygon area is output. The regular jurisdiction area, the event type, and the urgency level are input into the rule table engine. The rule table engine performs responsibility analysis on the time and outputs the dual responsibility factor.

[0032] Furthermore, the dual responsibility factors include: responsibility matching factor and spatiotemporal responsibility factor; if the time is a regular period, the rule table engine constructs an inherent static responsibility rule table based on the responsibility matching list in the GIS geographic information database, and determines the responsibility matching factor of the reported event from the inherent static responsibility rule table according to the regular jurisdiction area and the event type, and outputs it; If the time is an unusual time, the rule table engine constructs a spatiotemporal temporary responsibility rule table based on the special activity information, determines the spatiotemporal responsibility factor of the reported event from the spatiotemporal temporary responsibility rule table based on the dynamic polygon region, the event type, and the urgency level, and outputs it.

[0033] For regular time periods, standard city grids and street boundaries can be directly matched to generate regular management areas. For irregular time periods (such as holidays or periods with large-scale events), time intervals, spatial polygons, and support area lists are extracted from holiday duty plans and large-scale event support notices and registered as the smallest configuration unit in the GIS rule base. When the timestamp of a reported event falls within the validity period of the contingency plan and the event location falls within the corresponding temporary polygon, the system replaces the regular management area with the temporary polygon and includes the whitelisted areas in the candidate disposal set. Furthermore, based on the dynamic polygon area, the system searches the background area status database to filter out the candidate disposal area set that meets two core conditions: it is within the jurisdiction of the dynamic polygon, and the terminal is online and in a workable state. Offline, vacation, and task-shutdown disposal units are eliminated to narrow down the evaluation scope of subsequent algorithms.

[0034] This invention constructs a dual-mode management area adaptation mechanism for conventional grids and dynamic contingency plans, enabling flexible switching of jurisdictional boundaries. By automatically extracting time, space, and area information from holiday duty plans and large-scale event support notices and registering them as temporary polygons, the system can dynamically match the optimal jurisdictional scope according to the spatiotemporal attributes of events. Furthermore, it combines the online status and working status of the area for dual screening, eliminating unusable disposal units and effectively narrowing the candidate set size, laying a precise and efficient data foundation for subsequent intelligent dispatching.

[0035] Step S30: Construct a distance factor based on the dynamic polygon region, construct a load factor and a historical performance factor based on the service data input by the user, and determine multiple weight matching coefficients based on the event attribute information. Based on all the weight matching coefficients, calculate the comprehensive score of each candidate region according to the dual responsibility factor, the distance factor, the load factor and the historical performance factor.

[0036] This invention relies on a two-layer architecture of static inherent rights and responsibilities rule tables and spatiotemporal temporary rights and responsibilities rule tables. It takes three conditions as input: event type, dynamic polygon region, and reporting time. It calculates and outputs two independent rights and responsibilities evaluation factors in parallel, decoupling long-term statutory functions from short-term temporary permissions. It also calculates three general scheduling factors: distance, load, and historical performance. It does not require manual modification of the basic rights and responsibilities configuration, provides standard data support for weighted scoring, and automatically adapts to the transfer of functions and support scheduling in special scenarios such as holidays and large-scale events, filling the scenario gap of traditional fixed rights and responsibilities scheduling.

[0037] Specifically, a distance factor is constructed based on the dynamic polygon region: ; in, Represents the distance factor. This represents the path between the candidate region and the verification latitude and longitude coordinates. This represents the farthest path from the check latitude and longitude coordinates within the candidate region set. For each candidate region, obtain the business data of the candidate region, calculate the equivalent load value of the candidate region based on the current number of valid pending work orders and the number of completed work orders for the day in the business data, and construct a load factor based on the equivalent load value: ; in, Indicates the equivalent load value. This indicates the number of currently active work orders. Indicates the fatigue coefficient. This indicates the number of work orders completed that day; ; in, Indicates the load factor. This indicates the preset maximum load threshold; For each candidate region, all historical closed work orders within a preset time period are obtained, and the processing data of the same secondary category events as each historical closed work order are statistically analyzed to obtain the average processing time, first-time completion rate, user satisfaction rate, and rework / redispatch rate. Calculate the timeliness score based on the average processing time and the longest average processing time in the candidate region set: ; in, Indicates the timeliness score. Indicates the average processing time. Indicates the longest average processing time; Calculate the quality score of the candidate region based on the first-time completion rate, the user satisfaction rate, and the rework / redispatch rate: ; in, Indicates the quality score. This indicates the one-time completion rate. Indicates user satisfaction rate. Indicates the rework and reassignment rate; The timeliness score and the quality score are weighted and fused to obtain the historical performance factor of the candidate region: ; in, This represents the historical performance factor.

[0038] This includes a database of activity information for the reported event's location, and the construction of a static, inherent responsibility rule table. This table features a four-level mapping: event category, event subcategory, candidate region, and responsibility level, with values ​​directly assigned according to the responsibility level. .

[0039] Furthermore, based on holiday duty schedules, large-scale event support notices, and temporary information, a spatiotemporal temporary authority and responsibility rule table is constructed. These are rules that are effective in stages. Each rule contains six core fields: effective time interval, effective geofence, list of authorized departments, authorization level, covered event types, and rule priority. Values ​​are assigned according to the authorization level. ; Setting effective and expiration timestamps within the rules helps the system automatically verify time and spatial dimensions. If a match is found, the temporary rule takes effect and expires automatically. It's important to note that for rules that simultaneously meet these criteria... For 0 and If the value is 0.2, the region will be directly removed from the candidate set and no work order will be assigned to that region.

[0040] This invention standardizes and encodes complex event classifications and regional responsibility relationships, enabling rapid and accurate matching of rights and responsibilities. This avoids the performance overhead of dynamic calculations. The four-level mapping ensures fine-grained rule coverage while facilitating subsequent maintenance and expansion, providing stable and reliable underlying data support for automatic work order dispatch. Simultaneously, a spatiotemporal temporary rights and responsibilities rule table is established. Through six core fields, including effective time interval, geofence, and authorized department, it enables flexible configuration and automatic management of phased special rules. The built-in timestamp mechanism allows rules to automatically take effect and expire according to settings without manual intervention, significantly reducing operational complexity during holidays and large-scale events. While ensuring the stability of regular work order dispatch, it provides a rapid response and elastic expansion capability for sudden and temporary management needs. Finally, the introduction of rule priority and dual-condition judgment mechanisms effectively solves the conflict problem when regular and temporary rules coexist.

[0041] Furthermore, a preset weight configuration table is obtained, and multiple weight matching coefficients are determined from the weight configuration table according to the event type and urgency. The dual-responsibility factor, the distance factor, the load factor, and the historical performance factor are weighted according to all the weight matching coefficients to calculate the comprehensive score of each candidate region: ; in, This indicates the overall score. Represents the distance factor. express The weighted matching coefficient, Indicates the load factor. express The weighted matching coefficient, Indicates the responsibility matching factor. express The weighted matching coefficient, Represents historical performance factor. express The weighted matching coefficient, Indicates the spatiotemporal responsibility factor. express The weighted matching coefficient.

[0042] In the embodiments disclosed in this invention, four types of standard scene weight sets are predefined. The system automatically matches the corresponding weight set according to the event urgency level, event secondary classification, and whether the temporary spatiotemporal rule is hit, and substitutes it into the comprehensive scoring formula to calculate the total score of the candidate region. The specific rules are shown in Table 1. Table 1: Weighting Allocation Table

[0043] As shown in Table 1, in emergency scenarios, distance weight can be amplified to prioritize nearby handling; in patent-related time scenarios, inherent responsibility weight can be amplified to prioritize matching with dedicated departments; in temporary spatiotemporal scenarios, spatiotemporal responsibility and load weights are amplified while inherent weights are weakened to support cross-regional support and temporary diversion; for routine scenarios, load, efficiency, and responsibility are balanced to adapt to daily grid management. Specifically, amplifying distance weight in emergency scenarios ensures rapid response, strengthening inherent responsibility in patent scenarios ensures clear attribution, weakening routine rules in temporary scenarios supports cross-regional collaboration, and balancing multi-dimensional indicators in routine scenarios adapts to refined management. This design simplifies complex multi-objective decision-making into a scenario-driven weight adjustment mechanism, enabling the system to adaptively generate the optimal dispatch strategy under different business demands, combining flexibility and interpretability.

[0044] Step S40: Select the target area from all the candidate areas based on all the comprehensive scores, construct a dispatch instruction based on the time location information and event attribute information, and send the dispatch instruction to the target area to dispatch the order.

[0045] Specifically, all the comprehensive scores are sorted to obtain a candidate region sorting list; The first preliminary selection area is selected from the candidate area sorting list, and a dispatch instruction is constructed based on the time location information and event attribute information. The dispatch instruction is then sent to the preliminary selection area. If the initial selection area does not receive the dispatch instruction, the dispatch instruction is sent to the second initial selection area ranked second, until a candidate area receives the dispatch instruction, then the candidate area is defined as the target. If none of the candidate regions in the candidate region sorting list have received the dispatch instruction, the dispatch instruction will be forwarded to the administrator for manual dispatch.

[0046] After completing the multi-factor weighted scoring and ranking, the system outputs a ranked list of candidate regions. The system will select the region with the highest score to generate a dispatch order. The dispatch order adds a processing region and synchronously links the full business details of the original work order.

[0047] Furthermore, to address order dispatch failures, this invention incorporates multiple fallback mechanisms. If the optimal handling unit fails to acknowledge the order within a preset 15-second period (the threshold can be customized), the system automatically triggers a secondary backup plan, transferring the order to the candidate department with the second-highest score, thus preventing unclaimed tasks and interrupted processing. Additionally, if all regions in the candidate list reject the work order, or if the overall algorithm score falls below a preset threshold for complex cross-cutting events, the system suspends automatic order dispatch and pushes the data to the central control screen for manual arbitration, where a specialist assesses and handles the situation, balancing automation efficiency with adaptability to complex scenarios. If a timeout reassignment or manual arbitration fallback mechanism is triggered, supplementary data such as the order type, trigger reason, and workflow record are generated simultaneously, ensuring full traceability throughout the process.

[0048] Furthermore, the present invention discloses another embodiment to illustrate the entire execution process: During the normal time period, if the reported event does not match any temporary control rules, a dynamic polygon area of ​​the regular grid of Street A is generated. Four candidate areas (area a, area b, area c, and area d) within the jurisdiction are selected and then matched with the static inherent responsibility table to obtain the factor values ​​of each department: , ,

[0049] Among them, region a =1, If the value is 0.2, the candidate region is determined to be retained; region b and The values ​​are 0.3 and 0.2 respectively, and are also retained; region c and If the values ​​are 0 and 0.2 respectively, then region c should be removed; region d... and The values ​​are 0.3 and 0.2 respectively, and are retained.

[0050] Then, multi-factor normalization calculations were performed, and the remaining dimensional factors were calculated for the remaining regions a, b, and d. The specific results are shown in Table 2. Table 2: Factor Results Table

[0051] If the reported event is classified as a regular event scenario, the matching coefficients of each factor weight can be determined, and the comprehensive score of each candidate region can be calculated. Finally, the score results of region a are 0.74, region b are 0.5675, and region d are 0.555. At this point, the three regions can be sorted according to the scores, and a dispatch instruction can be generated and sent to region a for dispatch.

[0052] This invention retains the stable multi-factor scoring logic while introducing a spatiotemporal weighting mechanism to achieve intelligent dispatching driven by urban management event data, spatiotemporal adaptation, AI decision-making, and dynamic optimization, thereby improving dispatching accuracy and efficiency.

[0053] Furthermore, such as Figure 3 As shown, based on the above-mentioned intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation, the present invention also provides an intelligent dispatching system for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation, wherein the intelligent dispatching system for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation includes: The simulation network construction module 51 is used to acquire development data and decision data of all cities in a preset area within a preset time, quantify the decision data to obtain a quantification result, determine multiple nodes based on the quantification result, input the development data and the decision data into the corresponding nodes, and construct a simulation network based on the nodes. The node determination module 52 is used to analyze the development data and decision data in all the nodes, obtain the analysis results, obtain the correlation information between multiple nodes based on the analysis results, determine the associated nodes that are associated based on the correlation information, determine multiple sets of node connection relationships based on the multiple associated nodes, and obtain the number of node connection relationship groups. The average betweenness centrality calculation module 53 is used to calculate the degree of association between multiple nodes based on the association information and the number of node connection relationship groups, and to calculate the average betweenness centrality of the simulated network based on the degree of association. The result acquisition module 54 is used to construct a result analysis model. It inputs the development data, the number of nodes of the nodes, the number of node connection groups, and the average intermediary centrality into the result analysis model and outputs the simulation results of urban development differences.

[0054] Furthermore, such as Figure 4 As shown, based on the above-mentioned intelligent dispatching method and system for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation, the present invention also provides a terminal, which includes a processor 10, a memory 20 and a display 30. Figure 4 Only some of the terminal components are shown; however, it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0055] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory. In other embodiments, the memory 20 may be an external storage device of the terminal, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc. Further, the memory 20 may include both internal and external storage devices. The memory 20 is used to store application software and various types of data installed on the terminal, such as program code installed on the terminal. The memory 20 can also be used to temporarily store data that has been output or will be output. In one embodiment, the memory 20 stores a spatiotemporally dynamic rights and responsibilities-adapted intelligent dispatching program 40 for urban management events. This program 40 can be executed by the processor 10, thereby implementing the spatiotemporally dynamic rights and responsibilities-adapted intelligent dispatching method for urban management events in this application.

[0056] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor, or other data processing chip, used to run program code stored in the memory 20 or process data, such as executing the intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation.

[0057] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display 30 is used to display information on the terminal and to display a visual user interface. The components of the terminal communicate with each other via a system bus.

[0058] In one embodiment, when the processor 10 executes the urban management event intelligent dispatch program 40 based on spatiotemporal dynamic rights and responsibilities adaptation in the memory 20, it implements the steps of the urban management event intelligent dispatch method based on spatiotemporal dynamic rights and responsibilities adaptation as described above.

[0059] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores an intelligent dispatch program for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation, and when the intelligent dispatch program for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation is executed by a processor, it implements the steps of the intelligent dispatch method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation as described above.

[0060] In summary, this invention provides an intelligent dispatching method and related equipment for urban management events based on spatiotemporal dynamic responsibility adaptation. The method includes: acquiring reported events input by users; constructing standardized work orders based on the reported events; inputting the standardized work orders into a pre-constructed information extraction model for compliance verification; and outputting time and location information and event attribute information; inputting the time and location information into a GIS fence engine for analysis; outputting a dynamic polygonal region of the reported events; inputting the event attribute information into a rule table engine for analysis; and outputting dual responsibility factors; constructing a distance factor based on the dynamic polygonal region; constructing a load factor and a historical performance factor based on user-input business data; determining multiple weight matching coefficients based on the event attribute information; calculating a comprehensive score for each candidate region based on all the weight matching coefficients, the dual responsibility factors, the distance factor, the load factor, and the historical performance factor; selecting a target region from all the candidate regions based on all the comprehensive scores; constructing a dispatching instruction based on the time and location information and the event attribute information; and sending the dispatching instruction to the target region for dispatching. This invention retains the stable multi-factor scoring logic while introducing a spatiotemporal weighting mechanism to achieve intelligent dispatching driven by urban management event data, spatiotemporal adaptation, AI decision-making, and dynamic optimization, thereby improving dispatching accuracy and efficiency.

[0061] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal that includes that element.

[0062] Of course, those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.). The program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The computer-readable storage medium can be a memory, magnetic disk, optical disk, etc.

[0063] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A method for intelligent dispatching of urban management events based on spatiotemporal dynamic rights and responsibilities adaptation, characterized in that, The intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation includes: The system acquires user-inputted reported events, constructs standardized work orders based on these events, inputs the standardized work orders into a pre-constructed information extraction model for compliance verification, and outputs time location information and event attribute information. The time and location information is input into the GIS fence engine for analysis, and the dynamic polygonal area of ​​the reported event is output. The event attribute information is input into the rule table engine for analysis, and the dual responsibility factor is output. A distance factor is constructed based on the dynamic polygon region, a load factor and a historical performance factor are constructed based on the business data input by the user, and multiple weight matching coefficients are determined based on the event attribute information. Based on all the weight matching coefficients, a comprehensive score for each candidate region is calculated based on the dual responsibility factor, the distance factor, the load factor and the historical performance factor. The target region is selected from all the candidate regions based on the comprehensive scores, and a dispatch instruction is constructed based on the time location information and event attribute information. The dispatch instruction is then sent to the target region for dispatching.

2. The intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation as described in claim 1, characterized in that, The process of acquiring user-inputted reporting events, constructing standardized work orders based on these events, inputting the standardized work orders into a pre-built information extraction model for compliance verification, and outputting time location information and event attribute information specifically includes: Obtain the reported events input by the user, and construct an original work order based on all the reported events. The original work order includes latitude and longitude, secondary category of the event, reporting time and event description information. The latitude and longitude, the secondary category of the event, and the reporting time are verified for completeness. The event description information is completed by field completion. Based on the completed latitude and longitude and time, it is determined whether the reported event is a valid work order. If it is a valid work order, then the secondary category of the reported event is matched. If the match fails, it is returned to the primary category for reassignment until a match is successful, and the event type of the reported event is obtained. Based on the verification latitude and longitude, the time, and the event type, determine whether the reported event is a duplicate work order; if not, construct a standardized work order for the reported event. The standardized work order is input into the information extraction model for information classification, and the time and location information and event attribute information of the reported event are output.

3. The intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation according to claim 2, characterized in that, The process of inputting the time and location information into a GIS fence engine for analysis, outputting a dynamic polygonal region of the reported event, and inputting the event attribute information into a rule table engine for analysis, outputting dual-responsibility factors, specifically includes: The verification latitude and longitude and the time are input into the GIS fence engine for analysis; If the time is a regular period, the regular jurisdiction area where the reported event is located is determined based on the verified latitude and longitude. If the time is an irregular time, the dynamic polygon area where the verified latitude and longitude is located during the time period is determined based on the special activity information in the GIS geographic information database, and the regular jurisdiction area or the dynamic polygon area is output. The regular jurisdiction area, the event type, and the urgency level are input into the rule table engine. The rule table engine performs responsibility analysis on the time and outputs the dual responsibility factor.

4. The intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation according to claim 3, characterized in that, The dual responsibility factors include: responsibility matching factor and spatiotemporal responsibility factor; The process of inputting the regular jurisdiction area, the event type, and the urgency level into the rule table engine, performing responsibility analysis on the time based on the rule table engine, and outputting the dual responsibility factor specifically includes: If the time period is a regular time period, the rule table engine constructs an inherent static responsibility rule table based on the responsibility matching list in the GIS geographic information database, and determines the responsibility matching factor of the reported event from the inherent static responsibility rule table according to the regular jurisdiction area and the event type, and outputs it; If the time is an unusual time, the rule table engine constructs a spatiotemporal temporary responsibility rule table based on the special activity information, determines the spatiotemporal responsibility factor of the reported event from the spatiotemporal temporary responsibility rule table based on the dynamic polygon region, the event type, and the urgency level, and outputs it.

5. The intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation according to claim 1, characterized in that, The step of constructing a distance factor based on the dynamic polygon region and constructing a load factor and historical performance factor based on user-input service data specifically includes: Construct a distance factor based on the dynamic polygon region: ； in, Represents the distance factor. This represents the path between the candidate region and the verification latitude and longitude coordinates. This represents the farthest path from the check latitude and longitude coordinates within the candidate region set. For each candidate region, obtain the business data of the candidate region, calculate the equivalent load value of the candidate region based on the current number of valid pending work orders and the number of completed work orders for the day in the business data, and construct a load factor based on the equivalent load value: ； in, Indicates the equivalent load value. This indicates the number of currently active work orders. Indicates the fatigue coefficient. This indicates the number of work orders completed that day; ； in, Indicates the load factor. This indicates the preset maximum load threshold; For each candidate region, all historical closed work orders within a preset time period are obtained, and the processing data of the same secondary category events as each historical closed work order are statistically analyzed to obtain the average processing time, first-time completion rate, user satisfaction rate, and rework / redispatch rate. Calculate the timeliness score based on the average processing time and the longest average processing time in the candidate region set: ； in, Indicates the timeliness score. Indicates the average processing time. Indicates the longest average processing time; Calculate the quality score of the candidate region based on the first-time completion rate, the user satisfaction rate, and the rework / redispatch rate: ； in, Indicates the quality score. This indicates the one-time completion rate. Indicates user satisfaction rate. Indicates the rework and reassignment rate; The timeliness score and the quality score are weighted and fused to obtain the historical performance factor of the candidate region: ； in, This represents the historical performance factor.

6. The intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation according to claim 2, characterized in that, The step of determining multiple weighted matching coefficients based on the event attribute information, and calculating a comprehensive score for each candidate region based on all the weighted matching coefficients, according to the dual responsibility factor, the distance factor, the load factor, and the historical performance factor, specifically includes: Obtain a preset weight configuration table, and determine multiple weight matching coefficients from the weight configuration table according to the event type and urgency. The dual-responsibility factor, the distance factor, the load factor, and the historical performance factor are weighted according to all the weight matching coefficients to calculate the comprehensive score of each candidate region: ； in, This indicates the overall score. Represents the distance factor. express The weighted matching coefficient, Indicates the load factor. express The weighted matching coefficient, Indicates the responsibility matching factor. express The weighted matching coefficient, Represents historical performance factor. express The weighted matching coefficient, Indicates the spatiotemporal responsibility factor. express The weighted matching coefficient.

7. The intelligent dispatching method for urban management events based on spatiotemporal dynamic responsibility adaptation according to claim 1, characterized in that, The step of filtering the target region from all candidate regions based on all the comprehensive scores, constructing a dispatch instruction based on the time location information and event attribute information, and sending the dispatch instruction to the target region for dispatching the order specifically includes: Sort all the comprehensive scores to obtain a candidate region sorting list; The first preliminary selection area is selected from the candidate area sorting list, and a dispatch instruction is constructed based on the time location information and event attribute information. The dispatch instruction is then sent to the preliminary selection area. If the initial selection area does not receive the dispatch instruction, the dispatch instruction is sent to the second initial selection area ranked second, until a candidate area receives the dispatch instruction, then the candidate area is defined as the target. If none of the candidate regions in the candidate region sorting list have received the dispatch instruction, the dispatch instruction will be forwarded to the administrator for manual dispatch.

8. A smart dispatching system for urban management events based on spatiotemporal dynamic responsibility adaptation, characterized in that, The urban management event intelligent dispatch system based on spatiotemporal dynamic responsibility adaptation is used to implement the urban management event intelligent dispatch method based on spatiotemporal dynamic responsibility adaptation as described in any one of claims 1-7, wherein the urban management event intelligent dispatch system based on spatiotemporal dynamic responsibility adaptation includes: The information reporting module is used to obtain the reporting events input by the user, construct a standardized work order based on the reporting events, input the standardized work order into the constructed information extraction model for compliance verification, and output time location information and event attribute information. The factor analysis module is used to input the time and location information into the GIS fence engine for analysis, output the dynamic polygon area of ​​the reported event, input the event attribute information into the rule table engine for analysis, and output the dual responsibility factor. The weight matching and scoring module is used to construct a distance factor based on the dynamic polygon region, construct a load factor and a historical performance factor based on the business data input by the user, determine multiple weight matching coefficients based on the event attribute information, and calculate a comprehensive score for each candidate region based on all the weight matching coefficients, the dual responsibility factor, the distance factor, the load factor and the historical performance factor. The dispatch module is used to filter out the target area from all the candidate areas based on all the comprehensive scores, construct the dispatch instruction based on the time location information and event attribute information, and send the dispatch instruction to the target area for dispatching.

9. A terminal, characterized in that, The terminal includes: a memory, a processor, and an intelligent dispatching program for urban management events based on spatiotemporal dynamic rights and responsibilities, stored in the memory and executable on the processor. When the intelligent dispatching program for urban management events based on spatiotemporal dynamic rights and responsibilities is executed by the processor, it implements the steps of the intelligent dispatching method for urban management events based on spatiotemporal dynamic rights and responsibilities as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores an intelligent dispatch program for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation. When the intelligent dispatch program for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation is executed by a processor, it implements the steps of the intelligent dispatch method for urban management events based on spatiotemporal dynamic rights and responsibilities adaptation as described in any one of claims 1-7.

Images