Community event processing method, system and terminal

Abstract

The invention relates to a community event processing method and system and a terminal, and belongs to the technical field of data processing.The community event processing method comprises the steps that event information reported by a grid member is received; a feature vector is generated according to the event information, a corresponding weight is matched for each feature in the feature vector, and the features in the feature vector comprise the number of people involved in the public, the cross-department relevance and the emergency degree; calculating a comprehensive event value according to the feature vector and the weight of feature matching; generating a routing decision result according to the comprehensive event value; and assigning the assembled event task packet according to the routing decision result. The method has the beneficial effects that events can be objectively evaluated and decided, and community management behaviors are standardized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a community event processing method, system and terminal. BACKGROUND

[0002] In today's society, community as the basic unit of people's life, its safety and stability is crucial. With the acceleration of urbanization process, community scale expands unceasingly, population structure is increasingly complex, various events occurring in the community are more and more frequent and diversified, such as infrastructure aging problem, noise problem, dog and bird raising problem, health problem, safety problem, etc. These events not only affect the quality of life of residents, but also may cause social contradictions and instability factors. Therefore, how to efficiently and scientifically process community events has become an important challenge faced by community management.

[0003] At present, in the aspect of community event processing, it mainly relies on community staff, grid staff, property company and owner committee, etc. When an event occurs in the community, the grid staff usually reports the event information to the community staff, and the community staff makes preliminary judgment and processing according to experience and relevant regulations. For some relatively simple events, such as neighborhood disputes, the community staff will solve them through mediation; while for some relatively complex events, such as infrastructure problems involving multiple departments, multiple departments need to be coordinated to process them.

[0004] However, this traditional community event processing method often relies on personal experience and subjective judgment to determine the severity of the event and the processing method, which is easy to lead to inaccuracy and unfairness of the processing result. For example, for some seemingly similar but actually different events, different processing methods may be taken due to the judgment bias of the staff, which may cause the dissatisfaction of residents. In addition, when coordinating multiple departments to process complex events, due to the lack of clear task allocation and responsibility definition, it is easy to appear shirking and wrangling phenomenon, which leads to low efficiency of event processing, and even may delay the best processing opportunity, causing greater loss. SUMMARY

[0005] In order to objectively evaluate and decide the event and standardize the community management behavior, the present application provides a community event processing method, system and terminal.

[0006] In a first aspect, the present application provides a community event processing method, which adopts the following technical scheme: A community event processing method, comprising: receiving event information reported by a grid staff; According to the event information, a feature vector is generated, and a corresponding weight is matched for each feature in the feature vector, the features in the feature vector including the number of stakeholders, cross-department relevance, and emergency level; According to the feature vector and the matched weight of the features, a comprehensive event value is calculated; According to the comprehensive event value, a routing decision result is generated; According to the routing decision result, the assembled event task package is dispatched.

[0007] By adopting the above technical solution, the event information is converted into a feature vector containing features such as the number of stakeholders, cross-department relevance, and emergency level, and a corresponding weight is matched for each feature, and then a comprehensive event value is calculated, which avoids the subjectivity and randomness of human judgment and can more objectively and accurately evaluate the severity and complexity of the event. Based on the comprehensive event value, a routing decision result is generated, which can accurately dispatch the event to the most suitable handling department or personnel according to the actual situation of the event, reducing the time for manual judgment and coordination in the traditional handling method, so that the event can be handled in the first time, especially for emergency events, which can greatly shorten the response time and reduce the loss caused by the event. In addition, according to the features and the comprehensive event value of the event, the human, material, and financial resources of the community can be reasonably allocated. For events with high emergency level and large number of stakeholders, more resources can be allocated for handling; while for relatively small events, less resources can be reasonably arranged to avoid waste of resources and improve the utilization efficiency of resources. This method clearly defines a series of processes from event reception to task dispatch, making community event handling have rules to follow; grid members report event information according to the regulations, the system performs feature extraction, weight matching, comprehensive event value calculation, and routing decision according to the preset rules, and each link has clear standards and requirements, which helps to standardize community management behavior.

[0008] Optionally, the step of generating a feature vector according to the event information comprises: According to the event information, the number of directly affected people and the number of event-related departments are obtained; According to the number of directly affected people and the total population of the community grid, a stakeholder factor of the number of stakeholders is calculated; According to the event information and a preset event type mapping table, an emergency mapping value of the emergency level is obtained; According to the number of event-related departments and the total number of registered departments, a relevance value of cross-department relevance is calculated; According to the stakeholder factor, the emergency mapping value, and the relevance value, a feature vector of the event is generated.

[0009] By adopting the technical scheme, the influence degree of the event on the community residents can be quantified by calculating the stakeholder factor of the number of stakeholders, which helps the community manager to determine the priority and resource allocation according to the influence range of the event, and ensures the effective use of resources. The emergency mapping value of the emergency degree can standardize different types of emergency events, so that the processing of the emergency events can follow unified standards, and the timeliness and accuracy of the processing are improved. The correlation value of the cross-department correlation helps to clarify the participation degree of each department in the event processing, optimizes task scheduling and resource allocation, and avoids processing delay caused by poor communication between departments.

[0010] Optionally, the step of generating a routing decision result according to the comprehensive event value comprises: determining whether the comprehensive event value is less than a first set event value; if yes, obtaining a real-time load rate of a grid member; generating a first routing decision result according to the real-time load rate; if no, generating a second routing decision result.

[0011] By adopting the technical scheme, when the comprehensive event value is less than the first set event value, the real-time load rate of the grid member is further obtained. The real-time load rate reflects the current busy degree of the grid member, and the first routing decision result is generated according to this index, which can allocate the event to the relatively idle grid member, avoid the situation that some grid members have too heavy tasks and some grid members are idle, make the workload of the grid members more balanced, and thus improve the efficiency and quality of the grid members in processing the event. For events with a comprehensive event value not less than the first set event value, a second routing decision result is directly generated, which can ensure that these complex events can be timely dispatched to the appropriate processing department or team, avoid the problem of untimely or improper processing caused by allocating complex events to grid members, and ensure that community events can be properly solved. The routing decision method considers the comprehensive situation of the event and the real-time working state of the grid member, and has strong flexibility and adaptability. The situation of community events is complex and changeable, and the characteristics of events and the workload of grid members may be different at different times and in different scenarios. This dynamic routing decision method can adjust the processing path of the event in real time according to the actual situation, better adapt to the actual needs of community event processing, and improve the efficiency of community management.

[0012] Optionally, the step of generating a first routing decision result according to the real-time load rate comprises: determining whether the real-time load rate is less than a load rate threshold value; if yes, the first routing decision result generated is DIRECT routing to a community grid member terminal; If not, the generated first routing decision result is BUBBLING routing to the street coordination center.

[0013] By adopting the above technical solutions, when it is judged that the real-time load rate is less than the load rate threshold, it indicates that the current workload of the grid member is within a bearable range, and there is enough energy and time to handle new community events. At this time, the decision result of "DIRECT routing to the community grid member terminal" is generated, which can make the event directly reach the grid member, reduce the circulation of intermediate links, enable the grid member to respond and handle the event quickly, and improve the timeliness of event handling. For example, for some common neighborhood disputes, minor environmental health problems, etc., the grid member can quickly and effectively solve the problem by relying on its familiarity with the community and the accumulation of daily handling experience, avoiding the complication of simple problems and improving the overall processing efficiency. If the real-time load rate is not less than the load rate threshold, it indicates that the grid member is already in a high-load working state and cannot bear new event handling tasks. In this case, the decision result of "BUBBLING routing to the street coordination center" is generated, and the event is transferred to the street coordination center. The street coordination center has more extensive resource allocation and coordination capabilities and can arrange personnel and resources to handle the event. It can coordinate multiple grid members to handle it together, or allocate the power of other related departments to participate, avoiding the decline in the quality of event handling or the delay in processing time caused by the overwork of the grid member, and ensuring that the event can be properly solved. Based on the real-time load rate of the grid member, the hierarchical processing is implemented, which embodies the scientificity and rationality of the community management architecture.

[0014] Optionally, the step of generating the second routing decision result comprises: judging whether the comprehensive event value is above a second set event value, the second set event value being greater than the first set event value; or, whether the association value is greater than an association threshold value; If yes, the second routing decision result is TUNNELING routing to the district-level command center; If not, the generated second routing decision result is BUBBLING routing to the street coordination center.

[0015] By adopting the technical scheme, when the comprehensive event value is above the second set event value or the correlation value is greater than the correlation threshold value, it is indicated that the event has high complexity, wide influence range and involves multiple departments, and the event may be a major community event across regions and departments, such as a large public safety event or an infrastructure construction problem involving multiple streets. At this time, the event is routed to the district-level command center in the "TUNNELING" mode, so that the event can quickly reach the district-level center with higher coordination capability and more resource allocation authority. The district-level command center can plan and coordinate from a macro perspective, and multiple streets and departments can participate in processing together, so as to avoid processing delay or improper processing due to insufficient coordination capability of the grassroots level, and ensure that the complex major event can be processed efficiently and professionally. If the above conditions are not met, it is indicated that the event has a relatively small complexity and influence range, and belongs to a general complex event, although the comprehensive event value is not less than the first set event value. The event is routed to the street coordination center in the "BUBBLING" mode, and the street coordination center can process the event based on its familiarity with the community situation in the street and certain coordination capability. In this way, the general event is prevented from being excessively moved up to the district-level command center, and the work burden of the district-level command center is reduced, and the event can be processed in time at a suitable level, and the processing efficiency is improved. The step further perfects the hierarchical management system of the community event processing, and clearly defines the responsibilities of the street coordination center and the district-level command center in processing different types of events. The street coordination center is responsible for processing general complex events and focuses on community management and coordination within the street; and the district-level command center focuses on processing complex major events and undertakes the coordination and decision-making responsibilities across streets and departments. The clear division of responsibilities helps to improve the work efficiency and professionalism of the management departments at all levels, and avoids the phenomenon of shirking responsibilities due to unclear responsibilities.

[0016] Optionally, the step of assigning the assembled event task package according to the routing decision result comprises: monitoring the task processing progress in real time; obtaining the task processing duration and the number of completed sub-tasks; judging whether the task processing duration is within the duration threshold to complete all tasks according to the number of completed sub-tasks; if not, automatically upgrading to the next level of administrator and redeploying low-load grid members.

[0017] By adopting the technical scheme, the progress of the event processing task can be grasped in real time by acquiring the task processing duration and the number of completed sub-tasks. This enables the community management department to have a clear understanding of the task processing speed and avoid delays in the task processing process. When it is judged that the task cannot be completed within the duration threshold, the task is automatically upgraded to a superior administrator. The superior administrator usually has more extensive resource allocation rights and higher decision-making authority, and can coordinate various forces from a more macro perspective to solve problems encountered in the task processing process. The low-load grid staff can be redeployed to participate in task processing, which can supplement the manpower required for task processing without increasing the cost of manpower. By upgrading the task and redeploying the grid staff in a timely manner, the existing management resources of the community can be fully utilized to avoid waste of resources.

[0018] Optionally, the community event processing method further comprises: After the event processing is completed, the response speed, resource utilization rate and public satisfaction are counted; The counted data is normalized to the [0, 1] interval, and a comprehensive performance value is calculated; It is judged whether the comprehensive performance value is lower than a performance threshold; If yes, a key mark is made; If the number of key marks of a certain type of event exceeds a set number, the weight of the feature vector corresponding to the event is dynamically adjusted.

[0019] By adopting the technical scheme, after the event processing is completed, the response speed, resource utilization rate and public satisfaction are counted. The response speed reflects the timeliness of the community's reaction to the event, the resource utilization rate reflects the use efficiency of manpower, material resources and other resources in the processing process, and the public satisfaction directly reflects the degree of recognition of the residents to the processing result. Through the data statistics of the three dimensions, the effect of event processing can be comprehensively and objectively evaluated to provide a basis for subsequent improvement. It is judged whether the comprehensive performance value is lower than the performance threshold, and if it is lower, a key mark is made. This helps the community management department to quickly identify events with poor processing effect and focus attention on the places that need to be improved, thereby improving the management efficiency. When the number of key marks of a certain type of event exceeds a set number, it indicates that there may be systematic problems in the processing process of this type of event. By dynamically adjusting the weight of the feature vector corresponding to this type of event, the decision mechanism of event processing can be optimized from the root cause and the processing effect can be improved.

[0020] In a second aspect, the present application provides a community event processing system, which adopts the following technical scheme: A community event processing system comprises: An event receiving module for receiving event information reported by a grid staff; An event processing module is configured to generate a feature vector according to the event information, match a corresponding weight for each feature in the feature vector, and calculate a comprehensive event value according to the feature vector and the matched weight; and generate a routing decision result according to the comprehensive event value. A task dispatching module is configured to dispatch the assembled event task package according to the routing decision result.

[0021] In a third aspect, the present application provides a terminal, which adopts the following technical solution. A terminal comprises: A memory storing a community event processing program; A processor configured to execute the program stored in the memory to implement the steps of the community event processing method.

[0022] In summary, the present application has at least the following advantages: The event information is converted into a feature vector containing features such as the number of stakeholders, cross-departmental relevance, and emergency level, and a corresponding weight is matched for each feature, and then a comprehensive event value is calculated, which avoids the subjectivity and randomness of human judgment and can more objectively and accurately assess the severity and complexity of the event. The routing decision result is generated based on the comprehensive event value, which can accurately dispatch the event to the most suitable processing department or personnel according to the actual situation of the event, reducing the time for manual judgment and coordination in the traditional processing method, so that the event can be processed in the first time, especially for emergency events, which can greatly shorten the response time and reduce the loss caused by the event. In addition, according to the features and comprehensive event value of the event, the human, material, and financial resources of the community can be reasonably allocated. For events with high emergency level and large number of stakeholders, more resources can be allocated for processing; while for relatively small events, less resources can be reasonably arranged to avoid waste of resources and improve the utilization efficiency of resources. This method clearly defines the series of processes from event reception to task dispatching, making the community event processing have rules to follow; grid members report event information according to the regulations, and the system performs feature extraction, weight matching, comprehensive event value calculation, and routing decision according to the preset rules, and each link has clear standards and requirements, which helps to standardize community management behavior. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 is a first flowchart of the method embodiment of the present application; Figure 2 is a second flowchart of the method embodiment of the present application; Figure 3 is a third flowchart of the method embodiment of the present application; Figure 4is a fourth flow chart of the method embodiment of the present application; Figure 5 is a fifth flow chart of the method embodiment of the present application. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the following will combine the accompanying drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application, and apparently, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application. Figure 1 - the accompanying drawings Figure 5 , the technical solutions in the embodiments of the present application are clearly and completely described. Apparently, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0025] The first embodiment of the present application discloses a community event processing method. Referring to Figure 1 , the community event processing method comprises S110-S150: S110, receiving event information reported by a grid member; S120, generating a feature vector according to the event information, and matching a corresponding weight for each feature in the feature vector, the features in the feature vector comprising a number of involved parties, cross-department correlation, and emergency level; S130, calculating a comprehensive event value according to the feature vector and the matched weight of the features; S140, generating a routing decision result according to the comprehensive event value; S150, dispatching an assembled event task package according to the routing decision result.

[0026] Specifically, in the S110 step of “receiving event information reported by a grid member”, the specific implementation manner is that: through the APP function of the mobile office sub-platform, the grid member can use a mobile terminal to report event details in real time during daily patrol, for example, by entering event type, location, and description information through the “event investigation” module of the APP; the reported data will be automatically transmitted to the data collection and management sub-platform for preliminary verification and storage (such as the geographic information database associated with the infrastructure database to ensure location accuracy), thereby seamlessly connecting the subsequent processing process.

[0027] Referring to Figure 2 , S120, the step of generating a feature vector according to the event information comprises S210-S250: S210, obtaining a number of directly affected people and a number of event-related departments according to the event information; S220, calculating an involved factor of the number of involved parties according to the number of directly affected people and the total population of the community grid; S230, obtaining an emergency mapping value of the emergency degree according to the event information and a preset event type mapping table; S240, calculating an association value of cross-department association according to the event association department number and the total number of registered departments; S250, generating a characteristic vector of the event according to the stakeholder factor, the emergency mapping value and the association value.

[0028] Specifically, in the S210 step "obtaining the number of directly affected people and the number of event association departments according to the event information", the system will automatically trigger the query mechanism of the infrastructure database based on the reported event information: for example, the number of affected residents is extracted from the population database by using the "house for people" function, and the department list related to the event (such as the association departments related to environmental protection events may include environmental protection bureau and village committee) is retrieved through the legal entity database, and the number of associated departments is calculated combined with the preset business rules to ensure real-time and accurate data and reduce manual intervention.

[0029] Then, the S220 step "calculating the stakeholder factor of the number of stakeholders according to the number of directly affected people and the total population of the community grid" relies on the linkage query of the population database and the geographic information database of the infrastructure database; the system automatically calls the total population data of the community grid (such as the number of registered residents of the current grid from the "grid staff" module of the population database), and obtains the stakeholder factor through a proportional calculation formula, which will be standardized to a value in the range of 0-1 to facilitate the generation of the subsequent characteristic vector; the calculation formula is the number of directly affected people divided by the total population multiplied by the population density correction factor (such as the population density correction factor of the suburbs is 0.8, and that of the city center is 1.2); this process is completed in the data collection and management sub-platform to support batch processing.

[0030] Then, in the S230 step "obtaining the emergency mapping value of the emergency degree according to the event information and a preset event type mapping table", the specific implementation is to use the preset rule engine of the intelligent dispatching sub-platform: the system automatically matches the preset event type mapping table in the data collection and management sub-platform according to the reported event type (such as fire or neighborhood dispute), the mapping table is set based on historical data analysis, for example, fire is mapped to high emergency value "0.9", and daily complaint is mapped to low value "0.3", the emergency mapping value is obtained in real time through API interface and stored in temporary cache to ensure response speed.

[0031] Next, the S240 step "calculating the association value of cross-department association according to the event association department number and the total number of registered departments" relies on the global data of the legal entity database; the system retrieves the total number of registered departments (such as the number of all registered units in the region), and then calculates the association value as a proportion (the number of event association departments divided by the total number of registered departments), the calculation logic is embedded in the task management module of the command and dispatching sub-platform to quantify the cross-department collaboration demand.

[0032] After that, in the step S250 of "generating the characteristic vector of the event according to the stakeholder factor, the emergency mapping value and the correlation value", the system constructs a multi-dimensional array structure (the characteristic vector contains three elements of the number of stakeholders, cross-department correlation and emergency degree) in the command and dispatch sub-platform, automatically generates the vector by integrating the calculation results of the previous steps, and normalizes the numerical values into a unified format, for example, using Python scripts or built-in functions, to facilitate subsequent weighted calculation.

[0033] Next, the implementation of "matching a corresponding weight for each feature in the characteristic vector" is based on the management strategy configuration of the platform; in the background setting of the command and dispatch sub-platform, the administrator can allocate values to each feature according to the preset weights (such as the stakeholder factor weight 0.4, the emergency degree 0.4 and the correlation value 0.2), and the weights are derived from the historical case learning of the data analysis sub-platform to ensure the scientificity of the decision.

[0034] Then, in the step S130 of "calculating the comprehensive event value according to the characteristic vector and the weight matched for the feature", the system automatically calculates using the weighted sum formula, for example, comprehensive event value = stakeholder factor × weight + emergency mapping value × weight + correlation value × weight, and the process is executed in real time in the core algorithm module of the command and dispatch sub-platform and the result is stored in the event task library.

[0035] Referring to Figure 3 , the step S140 of generating the routing decision result according to the comprehensive event value includes S310-S340: S310, judging whether the comprehensive event value is less than a first set event value; S320, if yes, acquiring the real-time load rate of the grid staff; S330, generating a first routing decision result according to the real-time load rate; S340, if no, generating a second routing decision result.

[0036] S330, the step of generating the first routing decision result according to the real-time load rate is as follows: judging whether the real-time load rate is less than a load rate threshold; if yes, the generated first routing decision result is the DIRECT routing to the community grid staff terminal; if no, the generated first routing decision result is the BUBBLING routing to the street coordination center.

[0037] S340, the step of generating the second routing decision result is as follows: If yes, the second routing decision result is TUNNELING routing to the district command center; if no, the second routing decision result is BUBBLING routing to the street coordination center.

[0038] Specifically, the step S310 of "judging whether the comprehensive event value is less than the first set event value" is realized by comparison logic: the system automatically compares the calculated value with the preset threshold (the first set event value is 0.5 for example), and the threshold is configured when the platform is initialized and can be dynamically adjusted. If it is less than, it enters the load rate checking link; if not, it jumps to the advanced judgment process.

[0039] Then, in the step S320 of "if the comprehensive event value is less than the first set event value, obtaining the real-time load rate of the grid staff", the implementation is to obtain the real-time load rate of the grid staff through the real-time monitoring function of the mobile office sub-platform. The system calls the current task queue data of the grid staff (such as the number of events to be processed and the completion rate displayed by the APP), calculates the load rate as a percentage value (for example, the number of tasks divided by the maximum capacity).

[0040] Then, "judging whether the real-time load rate is less than the load rate threshold" depends on the preset threshold rule (for example, the load rate threshold is set to 70%), and the system quickly evaluates in the command and dispatch sub-platform. If the load rate is low, the decision of "DIRECT routing to the community grid staff terminal" is generated, that is, the task is directly pushed to the to-do list of the grid staff's mobile phone APP to ensure quick response; if the load rate is high, the decision of "BUBBLING routing to the street coordination center" is generated, and the system automatically packages the event and forwards it to the workbench of the street center through the collaborative office sub-platform.

[0041] On the other hand, if it is judged that the comprehensive event value is not less than the first set event value, then in "judging whether the comprehensive event value is greater than the second set event value or the correlation value is greater than the correlation threshold", the system performs double condition comparison (the second set event value is 0.8 for example, and the correlation threshold is 0.6 for example), and triggers the decision based on the calculation result: if the condition is established, "TUNNELING routing to the district command center" is generated, and the system directly reports the event task package to the district platform through the direct channel of the intelligent dispatch sub-platform; if not, "BUBBLING routing to the street coordination center" is generated, and the event is distributed to the street level through the collaborative office sub-platform.

[0042] Finally, in the step "dispatch the assembled event task package according to the routing decision result" in S150, the implementation means that the command and dispatch sub-platform integrates event information, routing target and processing instructions, automatically assembles the task package (including event details, processing deadline, etc.), and distributes it to the corresponding terminal (such as the grid member APP or the street coordination center interface) through the push mechanism of the mobile office sub-platform, completes the entire event closed-loop processing, and updates the real-time display of the digital rural one map.

[0043] With reference to Figure 4 The steps after dispatching the assembled event task package according to the routing decision result include S410-S440: S410, real-time monitoring of task processing progress; S420, obtaining the task processing time and the number of completed sub-tasks; S430, determining whether the task processing time is within the time threshold to complete all tasks according to the number of completed sub-tasks; S440, if not, automatically upgrading to the next level of administrator and mobilizing low-load grid members.

[0044] Specifically, in the S410 "real-time monitoring of task processing progress" phase, after the task is dispatched, the system will track the event processing progress through the command and dispatch sub-platform. Each task package is decomposed into several sub-tasks, and the grid member updates the status in real time (such as uploading photos, checking completed steps) through the APP of the mobile office sub-platform. These dynamic data will be synchronized to the "event" module of the digital rural one map, and the processing progress will be visually displayed on the map with a color gradient. Management personnel can view the progress status marked by color at any time - green represents normal progress, and yellow indicates the risk of lag.

[0045] In the S420 "obtaining time and number of completions" link, the system will automatically trigger two sets of data analysis: on the one hand, the accurate time from task assignment to the current time is recorded through the timestamp, and on the other hand, the number of completed sub-tasks is counted by scanning the task decomposition structure. For example, when processing the "house safety hazard" event, the system will identify the completion proportion of sub-steps such as "on-site investigation → hazard identification → resident evacuation → construction reinforcement".

[0046] When S430 "determining overtime risk" is executed, the command and dispatch sub-platform calls the preset intelligent threshold system: for example, "emergency repair type" requires 3 core sub-tasks to be completed within 2 hours. If the repair work order has been in progress for 1.5 hours but only 1 item has been completed (such as only closing the valve without cleaning the accumulated water), the command and dispatch sub-platform will immediately trigger an early warning.

[0047] For the "automatic upgrade and personnel allocation" of S440, the platform adopts a dual-track response mechanism: one is to automatically upgrade the task to the next level administrator through the permission chain (such as transferring the grid member task to the street coordination center when the task is delayed), and the other is to retrieve the low-load grid member in the basic database in real time. For example, when a grid member's load rate reaches 85% due to an emergency (exceeding the threshold standard of 80%), the system will allocate a party member grid member participating in light party work from the party building sub-platform for support, and push the task instruction through the mobile office APP in seconds to ensure rapid resource restructuring. The whole process forms a "monitoring-diagnosis-intervention" closed loop; finally, the grid member response efficiency analysis chart is generated through the evaluation module of the party building sub-platform, providing data support for subsequent task assignment weight optimization.

[0048] Referring to Figure 5 The community event processing method further comprises: S510, after the event processing is completed, the response speed, resource utilization rate and public satisfaction are counted; S520, the counted data is normalized to the [0, 1] interval, and the comprehensive performance value is calculated; S530, whether the comprehensive performance value is lower than the performance threshold value is judged; S540, if yes, key marking is performed; S550, if the number of key markings of a certain type of event exceeds the set number, the weight of the feature vector corresponding to the event is dynamically adjusted.

[0049] Specifically, in the S510 step, after the event task package processing is completed, the system automatically triggers the performance statistics module: the response speed is calculated through the time stamp recorded by the command and dispatch sub-platform (the whole time consumption from S110 reporting to S150 dispatching); the resource utilization rate is based on the ratio of the number of event associated departments (S120) to the number of actual participating departments, and is associated with the department resource account in the legal person unit database; the public satisfaction is realized through the "take a picture" function of the mobile office sub-platform - the system pushes the star rating questionnaire to the people directly affected by the event (the residents located through the "people looking for housing" function), and combines the on-site verification feedback of the grid member.

[0050] Enter the S520 step, the data collection and management sub-platform dynamically normalizes the three types of indicators: the response speed is based on 24 hours as the reference value (more than 0), the resource utilization rate is based on the actual / plan resource ratio (the upper limit is 100% and 1), and the satisfaction is based on the 5-star system conversion (1 star = 0.2). The comprehensive performance value is calculated by the weight method (response speed 40% + resource utilization rate 30% + satisfaction 30%), and its numerical range is strictly limited to the [0, 1] interval.

[0051] S530-S540 links are automatically executed by the intelligent dispatching sub-platform: when the comprehensive performance value is lower than the preset threshold (such as 0.6), the system marks the event with a red warning mark in the "event layer" of the digital rural map, and at the same time, the event is included in the "key event analysis pool" of the infrastructure database. The performance threshold is obtained by training historical data, and the initial value can be set as the median of the sample event performance value.

[0052] The last S550 optimization mechanism embodies the system self-learning ability: the command and dispatching sub-platform scans the number of key marks of the same type of events (such as environmental protection type / public security type) per month. When the number of marks of a certain type of event exceeds the limit (such as 5 times), the weight dynamic adjustment algorithm is triggered - for example, the "emergency degree" weight of the environmental protection event that frequently exceeds the limit is automatically increased by 10%, and the "cross-department correlation" weight is reduced, so that the subsequent routing decision is more inclined to the TUNNELING direct report to the district center. The weight adjustment range is determined by regression analysis to ensure that the feature vector always reflects the actual governance needs.

[0053] The whole process deeply integrates the advantages of multi-platform cooperation: the mobile office sub-platform realizes data collection, the infrastructure database supports analysis and calculation, the digital rural map provides decision visualization, and finally the command and dispatching sub-platform completes strategy iteration to form a governance closed loop of "collection - disposal - evaluation - optimization".

[0054] Based on the above method embodiment, the second embodiment of the present application discloses a community event processing system. The community event processing system of the embodiment of the present application can realize any one of the above community event processing methods, and the specific working process of each module in the community event processing system can refer to the corresponding process in the above method embodiment.

[0055] For ease of understanding, an example is as follows: a community event processing system, comprising: An event receiving module is configured to receive event information reported by a grid member; An event processing module is configured to generate a feature vector according to the event information, and match a corresponding weight for each feature in the feature vector, wherein the features in the feature vector include the number of involved parties, cross-department correlation, and emergency degree; calculate a comprehensive event value according to the feature vector and the matched weight; and generate a routing decision result according to the comprehensive event value; A task dispatching module is configured to dispatch the assembled event task package according to the routing decision result.

[0056] The third embodiment of the present application provides a terminal, which can include a memory and a processor as an implementation manner of the terminal. The memory is configured to store a community event processing program; The processor is configured to execute a program stored in the memory to implement the steps of the community event processing method.

[0057] The memory can be in communication with the processor via a communication bus, which can be an address bus, a data bus, a control bus, or the like.

[0058] In addition, the memory can include a random access memory (RAM) and can also include a non-volatile memory (NVM), such as at least one disk memory.

[0059] The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), or the like; and can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, or the like.

[0060] The above are preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in the specification (including the abstract and drawings) can be replaced by other equivalent or similar features unless specifically stated. That is, each feature is only an example of a series of equivalent or similar features unless specifically stated.

Claims

1. A community event processing method, characterized by, The method comprises the following steps: receiving event information reported by a grid member; generating a feature vector according to the event information, and matching a corresponding weight for each feature in the feature vector, wherein the features in the feature vector include the number of involved people, cross-department correlation, and emergency level; calculating a comprehensive event value according to the feature vector and the matched weight; generating a routing decision result according to the comprehensive event value; dispatching an assembled event task package according to the routing decision result.

2. The community event processing method of claim 1, wherein, The step of generating a feature vector according to the event information comprises the following steps: obtaining the number of directly affected people and the number of event-related departments according to the event information; calculating a community factor of the number of involved people according to the number of directly affected people and the total population of the community grid; obtaining an emergency mapping value of the emergency level according to the event information and a preset event type mapping table; calculating a correlation value of the cross-department correlation according to the number of event-related departments and the total number of registered departments; generating a feature vector of the event according to the community factor, the emergency mapping value, and the correlation value.

3. The community event processing method of claim 1, wherein, The step of generating a routing decision result according to the comprehensive event value comprises the following steps: determining whether the comprehensive event value is less than a first set event value; if yes, obtaining a real-time load rate of the grid member; generating a first routing decision result according to the real-time load rate; if no, generating a second routing decision result.

4. The community event processing method of claim 3, wherein, The step of generating a first routing decision result according to the real-time load rate comprises the following steps: determining whether the real-time load rate is less than a load rate threshold value; if yes, the generated first routing decision result is a DIRECT routing to a community grid member terminal; if no, the generated first routing decision result is a BUBBLING routing to a street coordination center.

5. The community event processing method of claim 4, wherein, The step of generating a second routing decision result comprises the following steps: determining whether the comprehensive event value is greater than a second set event value, or whether the correlation value is greater than a correlation threshold value, wherein the second set event value is greater than the first set event value; if yes, the generated second routing decision result is a TUNNELING routing to a district-level command center; if no, the generated second routing decision result is a BUBBLING routing to a street coordination center.

6. The community event processing method of claim 1, wherein, The step after dispatching the assembled event task package according to the routing decision result comprises the following steps: real-time monitoring of the task processing progress; obtaining the duration of the task and the number of completed sub-tasks; determining whether the duration of the task is within a duration threshold value to complete all tasks according to the number of completed sub-tasks; if no, automatically upgrading to a higher-level administrator and redeploying a low-load grid member.

7. The community event processing method of claim 1, wherein, The community event processing method further comprises the following steps: after the event is processed, statistics of response speed, resource utilization rate, and public satisfaction; normalizing the statistical data to the [0, 1] interval and calculating a comprehensive performance value; determining whether the comprehensive performance value is lower than a performance threshold value; if yes, performing a key marking; if the number of key markings for a certain type of event exceeds a set number, dynamically adjusting the weight of the feature vector corresponding to the event.

8. A community event processing system characterized by, The method comprises the following steps: an event receiving module for receiving event information reported by a grid member; An event processing module is configured to generate a feature vector according to the event information, match a corresponding weight for each feature in the feature vector, and calculate a comprehensive event value according to the feature vector and the matched weight, wherein the features in the feature vector include the number of involved people, cross-department relevance, and urgency; and generate a routing decision result according to the comprehensive event value. A task dispatching module is configured to dispatch the assembled event task package according to the routing decision result.

9. A terminal, characterized by comprising: The community event processing method comprises the steps of: storing a community event processing program in a memory; executing the program stored in the memory by using a processor to implement the steps of the community event processing method according to any one of claims 1-7.

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