A smart response system for grassroots governance involving police and civilians, accessible via QR code.

Abstract

This invention relates to the field of police-civilian collaboration technology. Specifically, it relates to a smart response system for grassroots governance using QR codes, enabling police-civilian collaboration. The system includes a QR code reporting terminal unit, an intelligent central processing unit, a collaborative handling unit, a completion feedback unit, and an early warning and governance unit. The QR code reporting terminal unit provides a standardized governance QR code entry point with full coverage, allowing the public to access it via mobile phone scanning. It automatically matches the scanned code with the corresponding jurisdiction, responsible police officer, and grid worker. It receives governance requests and reports submitted by the public through multimodal methods, completes pre-verification of the requests, generates a standardized event form with a unique traceability code, and pushes it to the intelligent central processing unit. Through this three-tiered standardized governance QR code entry point with full coverage, the system completely breaks down the entry barriers of traditional digital governance systems. The public can directly access the service interface by scanning the code without downloading an app or registering.

Description

Technical Field

[0001] This invention relates to the field of police-civilian collaboration technology, specifically to a smart response system for grassroots governance that allows for online processing of administrative tasks in collaboration with the police. Background Technology

[0002] Grassroots social governance is an important cornerstone of the modernization of the national governance system and governance capacity. Police-community cooperation is a key vehicle for grassroots safety construction, conflict resolution, social security prevention and control, and convenient services to take root at the grassroots level.

[0003] Existing digital governance systems related to police-civilian collaboration primarily operate through fixed government service portals and online dedicated apps and mini-programs. These systems are mainly suited for routine government services, non-emergency police inquiries, and complaint reporting in fixed locations under non-emergency conditions. They rely heavily on citizens actively logging into fixed platforms to submit their requests. However, in grassroots governance scenarios where current technology is adapted, there are multi-dimensional technical deficiencies and application shortcomings. Citizen complaint reporting entry points are fragmented and have high barriers to entry, often involving multiple parallel codes, multiple platform redirects, and forced registration and login. Elderly and other vulnerable groups face a significant digital divide, and the systems lack security and reliability. The lack of an anonymous reporting mechanism has led to a situation where the public "doesn't know how to report, can't explain clearly, dares not report, and can't find the right person," resulting in limited channels and insufficient willingness for public participation in grassroots governance. Secondly, the handling process is inefficient and the responsibilities are unclear. Existing technologies rely heavily on manual classification and dispatch of requests, failing to achieve intelligent and rigid triage of police and non-police incidents. A large number of non-police incidents crowd out grassroots police resources. At the same time, the lack of a standardized hierarchical response time control mechanism easily leads to problems such as misallocation of dispatch orders, buck-passing, and overdue handling, making it impossible to achieve rapid response to emergencies. To reduce this situation, a smart response system for grassroots governance with police-civilian collaboration and QR code-based processing is proposed. Summary of the Invention

[0004] The purpose of this invention is to provide a smart response system for grassroots governance involving police and the public, which solves the problems mentioned in the background.

[0005] To achieve the above objectives, a smart response system for grassroots governance involving police and the public is provided, comprising a QR code reporting terminal unit, an intelligent central processing unit, a collaborative handling unit, a completion feedback unit, and an early warning and governance unit. The QR code reporting terminal unit is used to provide a standardized governance QR code entry with full coverage, which can be accessed by the public through mobile phone scanning. It automatically matches the local jurisdiction, responsible police officer and grid member corresponding to the scanned code, receives governance requests and reports submitted by the public in a multimodal manner, generates a standardized event form with a unique traceability code after completing the request pre-verification, and pushes it to the intelligent middle platform processing unit. The intelligent middleware processing unit is used to receive event orders pushed by the QR code reporting terminal unit, complete the extraction of all event elements, type classification and risk classification through the pre-trained grassroots governance event analysis model, simultaneously complete the rigid diversion of police-related and non-police-related events, complete the second-level accurate dispatch of orders according to the preset hierarchical response rules, and simultaneously push the event handling order to the collaborative handling unit of the corresponding handling entity, while synchronizing the entire process data of the event to the early warning and governance unit. The collaborative handling unit is used to receive event handling orders pushed by the intelligent middle platform processing unit, trigger the corresponding level of response mechanism, provide a mobile handling port for front-line handling personnel, realize cross-departmental collaborative scheduling, on-site evidence collection, real-time feedback of the handling process and automatic generation of handling reports, and simultaneously synchronize the data of the entire handling process nodes to the completion feedback unit and the early warning management unit in real time. The completion feedback unit is used to receive data from the handling nodes, synchronize the progress of the entire event handling process to the public, and complete the dual verification of AI and human verification after receiving the completion application submitted by the handling personnel. After the verification is passed, the completion result and satisfaction evaluation are pushed to the public. Based on the evaluation results, the event is archived in a closed loop or the process of returning the case for re-handling is triggered. At the same time, the completed archived data is synchronized to the early warning and management unit. The early warning and governance unit is used to receive and accumulate full-process event data, build a special database and governance profile for grassroots governance in the jurisdiction, complete the intelligent identification and hierarchical early warning of governance risks in the jurisdiction through the risk early warning model, push early warning information and prevention and control suggestions to the corresponding management entities in the jurisdiction, and at the same time complete the dynamic iterative optimization of system models and rules based on the full amount of data.

[0006] As a further improvement to this technical solution, the standardized governance QR code of the scanning and reporting terminal unit includes a three-level structure: a general fixed code for the jurisdiction, a building-specific binding code, and a police officer's personal service code. These codes are posted on smart doorplates, unit bulletin boards, community service points, and key locations within the jurisdiction. After scanning the code, the public can directly access the service interface without downloading an app or registering and logging in. The multimodal method of submitting requests includes reporting modes that support taking photos, recording videos, speaking, and inputting text. It has a built-in intelligent recognition module for multiple local dialects and minority languages, as well as a large-character adaptation mode for the elderly. Through a multimodal big data model, it automatically extracts the event type, geographical location, involved parties, and urgency level elements from the reported content and automatically completes and generates a standardized event form.

[0007] As a further improvement to this technical solution, the QR code reporting terminal unit has a built-in blockchain anonymous reporting submodule. It uses zero-knowledge proof encryption technology to encrypt the identity information of the whistleblower throughout the process. The reported event content is stored on the blockchain, which is tamper-proof and the identity of the whistleblower cannot be traced back. Only authorized personnel can view the event content. At the same time, it provides the whistleblower with an anonymous event progress query channel.

[0008] As a further improvement to this technical solution, the intelligent middleware processing unit, based on a pre-built knowledge graph of grassroots governance events, a list of responsibilities of multiple departments, and training and generation of police handling standards, can complete the full-element structured analysis of event orders, event type classification, and risk classification within 1 second; and achieve rigid diversion of police-related and non-police-related events, complete precise order dispatch within seconds according to preset hierarchical response rules, and automatically trigger hierarchical warnings and step-by-step supervision if the event is not handled within the time limit.

[0009] As a further improvement to this technical solution, the collaborative response unit has a built-in dynamic dispatch submodule for the response forces in the jurisdiction. Based on compliant location authorization, it constructs a real-time dynamic map of the police force, grid members, property security guards, social volunteers, and mobile grid members in the jurisdiction. In the event of emergencies and major incidents, it automatically dispatches the response forces closest to the scene to carry out initial control, personnel rescue and scene protection, and simultaneously transmits the scene situation back to build a 15-minute rapid response circle. It also has a built-in cross-departmental collaborative handling sub-module, which automatically forms an online collaborative handling team for complex events that cross fields and departments, connects the handling personnel of the corresponding functional departments, and realizes real-time sharing of event information, synchronous updates of handling progress, and clear division of handling tasks.

[0010] As a further improvement to this technical solution, the collaborative handling unit has a built-in AI-assisted document generation submodule, which can automatically generate standardized handling reports and work logs based on photos, videos and audio recordings collected on site, automatically complete the handling elements, and automatically archive the materials of the entire handling process to the public security police platform, grid management platform and government service platform, so as to achieve one-time entry and simultaneous retention in multiple systems. It also has a built-in blockchain evidence storage sub-module, which stores all nodes of the event handling process, operation records, evidence materials, and communication content on the blockchain to ensure that the data is tamper-proof, auditable, and traceable.

[0011] As a further improvement to this technical solution, the completion feedback unit adopts a courier-style progress tracking link. The public can view the event handling status, handling personnel, node progress, and completion time limit in real time through the original QR code entry. After each handling node is completed, progress reminders are automatically pushed to the public via WeChat and Alipay. The AI ​​and human dual verification process involves first using an AI verification model to compare images, check elements, and match handling standards to assess the effectiveness of the action. If the verification fails, the case is automatically returned to the handling personnel for further processing. Once the AI ​​verification is successful, the responsible police officer or grid worker will conduct a second manual review.

[0012] As a further improvement to this technical solution, in the completion feedback unit, after the double verification is passed, the completion result and star-level satisfaction evaluation entry are pushed to the public, and the event with the public's satisfaction rating is archived in a closed loop. For incidents that elicit negative public feedback, a mechanism for returning the case for reprocessing is automatically triggered. The superior management department initiates a special supervision process until the public approves the case and the case is archived. At the same time, the completed case file is simultaneously uploaded to the corresponding government and police systems for permanent storage.

[0013] As a further improvement to this technical solution, the early warning and governance unit can generate standardized governance profiles for each community, grid, and building within the jurisdiction, and quantitatively output core indicators such as safety index, hidden danger index, conflict index, and public satisfaction. The risk warning model can generate heat maps of events in the jurisdiction, spatiotemporal maps of high-incidence police incidents, and risk distribution maps based on full event data. It can accurately identify high-frequency hidden danger areas, high-incidence police incident locations, areas with frequent conflicts and disputes, and potential risks. According to the risk level, it can push warning information and rectification and prevention suggestions to the corresponding management entities. At the same time, it can provide data support for optimizing police patrol deployment, special investigation of hidden dangers, precise safety publicity, and early intervention in conflicts.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This smart response system for grassroots governance, which integrates police and public participation, completely breaks down the barriers to entry in traditional digital governance systems through a standardized three-tiered QR code system covering the entire region. Citizens can directly access the service interface by scanning the code without downloading an app or registering. It also features a multi-modal barrier-free reporting mode, adaptability for large fonts for the elderly, and intelligent dialect recognition, effectively bridging the digital divide for the elderly and other special groups. The built-in blockchain anonymous reporting sub-module uses zero-knowledge proof encryption technology to ensure end-to-end encryption and untraceability of the whistleblower's identity information, fundamentally addressing public concerns about being afraid to report or about leaks. This significantly lowers the threshold for expressing public demands, broadens the channels for police-public collaboration, effectively enhances public participation in grassroots governance, and lays a solid foundation for building a grassroots governance structure based on shared governance by all.

[0015] 2. This intelligent response system for grassroots governance, which integrates police and civilian efforts, achieves intelligent and efficient handling of grassroots governance incidents throughout the entire process through the coordinated operation of the intelligent central processing unit and the collaborative handling unit. Based on the knowledge graph of grassroots governance incidents and the analytical model trained on the list of responsibilities of multiple departments, it can complete the full-element analysis, classification and grading of incidents and accurate dispatch within 1 second. At the same time, it realizes the rigid separation of police-related and non-police-related incidents, allowing grassroots police officers to return to their primary responsibilities of police handling, effectively alleviating the problem of non-police-related incidents crowding out police resources. The supporting graded response rules and overdue warning and supervision mechanism set rigid time constraints for incident handling, effectively avoiding problems such as overdue handling and shirking responsibility. The collaborative response unit's built-in dynamic dispatching submodule for response forces can construct a real-time dynamic map of response forces within the jurisdiction, enabling nearby dispatch and initial response for emergency events, and building a 15-minute rapid response circle. The cross-departmental collaborative response submodule can automatically form online collaborative teams, breaking down data and collaboration barriers between departments. Meanwhile, the AI-assisted document generation submodule can automatically generate response reports and work ledgers, achieving one-time entry and simultaneous retention across multiple systems, significantly reducing the paperwork burden on grassroots staff. The blockchain evidence storage submodule enables on-chain evidence storage of the entire response process, ensuring that all operations are auditable and traceable, comprehensively improving the efficiency and standardization of grassroots event handling. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of a smart response system for grassroots governance with police-civilian collaboration via QR code, as described in this invention. Figure 2 This is a flowchart illustrating the process of the QR code scanning and reporting terminal unit of the present invention; Figure 3 This is a flowchart illustrating the intelligent middleware processing unit of the present invention. Figure 4 This is a flowchart illustrating the collaborative processing unit of the present invention; Figure 5 This is a flowchart illustrating the completion feedback unit of the present invention; Figure 6 This is a flowchart illustrating the early warning and management unit of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Please see Figures 1-6As shown, the purpose of this embodiment is to provide a smart response system for grassroots governance with police-civilian collaboration, including a QR code reporting terminal unit, an intelligent middleware processing unit, a collaborative handling unit, a completion feedback unit, and an early warning and governance unit. The QR code reporting terminal unit is used to provide a standardized governance QR code entry point with full coverage, which can be accessed by the public through mobile devices. It automatically matches the local jurisdiction, responsible police officer and grid member corresponding to the scanned code, receives governance requests and reports submitted by the public in a multimodal manner, and generates a standardized event form with a unique traceability code after completing the request pre-verification, and pushes it to the intelligent middle platform processing unit. The standardized governance QR code for the reporting terminal unit includes a three-level structure: a general fixed code for the jurisdiction, a building-specific binding code, and a police officer's personal service code. These codes are posted on smart doorplates, unit bulletin boards, community service points, and key locations within the jurisdiction. After scanning the code, the public can directly access the service interface without downloading an app or registering and logging in. First, a three-tiered standardized governance QR code system was established, consisting of a general fixed code for the jurisdiction, a building-specific binding code, and a police officer's personal service code. Each type of QR code was then linked to a specific location and responsible entity: the general fixed code for the jurisdiction was linked to the comprehensive governance center and the general duty room of the police station, adapting to the needs of public areas throughout the region. The building-specific binding code is based on the unit building as the smallest unit, and is one-to-one bound to the exclusive grid worker and the police officer in charge of the area; the police officer's personal service code is one-to-one bound to the corresponding police officer's area of ​​responsibility and police authority.

[0019] After the binding is completed, the three-level QR codes will be accurately posted to the corresponding scenarios. The general fixed code for the jurisdiction covers the community service hall, entrances and exits of key places, and public bulletin boards; the building-specific binding code covers the smart doorplates of the corresponding unit building, the bulletin board at the unit entrance, and the elevator; and the police officer's personal service code covers the community police bulletin board, the notice board of the area of ​​responsibility, and key industry places.

[0020] Finally, we completed the interface integration and testing between the QR code and the backend system to ensure that scanning the code can automatically parse the local code and the responsible entity ID. Simultaneously, we completed the backend deployment and functional integration and testing of the multimodal large model, the blockchain anonymous reporting sub-module, the dialect recognition module, and the large font adaptation module for the elderly, ensuring that all modules respond normally.

[0021] The public can scan the three-tier governance QR code posted on-site using the built-in scan function of WeChat, Alipay, or local government mini-programs, without needing to download a separate app or switch to a third-party application.

[0022] The system backend automatically verifies the legality of the QR code, identifying whether it is a valid governance QR code registered in the jurisdiction. If the verification fails, a compliance prompt will pop up and access will be terminated. If the verification passes, the system will automatically parse the local code and responsible entity ID in the QR code, match the corresponding local jurisdiction, responsible police officer and grid member information, and simultaneously complete the localization adaptation of the service interface. It will automatically load the high-frequency services and public information of the corresponding jurisdiction, without requiring the public to manually select the jurisdiction and contact department.

[0023] The system adopts a temporary session authorization mode, which does not require users to register an account or submit personal identity information to log in. It only obtains rough location permissions on the premise of voluntary authorization by the user. It does not forcibly collect private information such as mobile phone number or device number throughout the process, and directly jumps to the main service interface of the system, realizing access by scanning the code and zero threshold. The main service interface also has a quick entry to the accessibility mode. Users can switch to the elderly large font adaptation mode with one click, and simultaneously enable dialect voice guidance broadcast to adapt to the usage needs of special groups.

[0024] The system allows for multimodal submission of requests, including reporting modes that support taking photos, recording videos, speaking, and inputting text. It also features a built-in intelligent recognition module for multiple local dialects and minority languages, as well as a large-character adaptation mode for the elderly. Through a multimodal big data model, it automatically extracts elements such as event type, geographical location, involved parties, and urgency from the reported content and automatically completes and generates a standardized event form.

[0025] The QR code reporting terminal unit has a built-in blockchain anonymous reporting sub-module. It uses zero-knowledge proof encryption technology to encrypt the whistleblower's identity information throughout the process. The reported event content is stored on the blockchain, which is tamper-proof and the whistleblower's identity cannot be traced back. Only authorized personnel can view the event content. At the same time, it provides whistleblowers with an anonymous event progress query channel.

[0026] After entering the anonymous security reporting interface, the system first displays a full-screen anonymous security warning, clearly stating the security rules such as not collecting any identifiable information, encrypting and uploading the reported content to the blockchain, and ensuring immutability and traceability. After the user clicks to confirm and continue, the system automatically activates the encrypted environment on the user's local terminal. Throughout the process, it does not collect or upload any identifiable privacy data such as the user's mobile phone number, device ID, account information, or location information. At the same time, it generates a national-level asymmetric encryption public-private key pair on the user's local terminal. The private key is encrypted and stored on the user's local terminal and is not uploaded to any backend server. The public key serves as the unique anonymous identifier for this report and is bound to the reported content.

[0027] After the public submits their reports through multimodal means, the system uses a zero-knowledge proof encryption algorithm to generate a zero-knowledge proof of the validity of the report based on the local public-private key pair. This ensures that only the whistleblower holding the corresponding private key can supplement the content and check the progress, and authorized personnel can verify the validity of the report. The system makes it impossible to obtain or trace the identity information of the whistleblower throughout the entire process.

[0028] The system then synchronously writes the encrypted report content, zero-knowledge proof, anonymous public key, and reporting timestamp into the public security-comprehensive governance alliance blockchain node to complete the on-chain evidence storage. The on-chain data is tamper-proof, deletable, auditable, and traceable. No information that can identify the reporter's identity is stored throughout the process. At the same time, an anonymous event form is generated, which is only open to dedicated police officers in the local police station with exclusive viewing permissions. Other personnel without permissions cannot view it.

[0029] The system generates a local anonymous query credential for the whistleblower, which includes a 6-digit unique query code and a local private key matching verification rule. The whistleblower can use the original QR code entry to check the processing progress and supplement the whistleblower's evidence anonymously throughout the entire process, without submitting any identity information, by verifying the query code and local private key. Finally, the system pushes the anonymous event form to the intelligent middleware processing unit in real time with encryption, and simultaneously displays a successful submission notification, anonymous query credential, and saving instructions on the public's end, completing the entire anonymous reporting process.

[0030] The intelligent middleware processing unit is used to receive event orders pushed by the QR code reporting terminal unit. It completes the extraction of all event elements, type classification and risk classification through the pre-trained grassroots governance event analysis model. It simultaneously completes the rigid diversion of police and non-police events, completes the second-level accurate dispatching according to the preset hierarchical response rules, and pushes the event handling order to the corresponding handling entity's collaborative handling unit. At the same time, it synchronizes the entire event process data to the early warning and governance unit. In the intelligent middleware processing unit, based on the pre-built knowledge graph of grassroots governance events, the list of responsibilities of multiple departments and the training and generation of public security police handling standards, it can complete the full-element structured analysis of the event form within 1 second, and complete the event type classification and risk level classification. The system receives standardized or anonymous event forms from the QR code reporting terminal unit. After verifying the legality and integrity of the data, it enters the intelligent parsing stage. Based on the pre-built knowledge graph of grassroots governance events, the list of responsibilities of multiple departments, and the police handling standards, it calls the trained intelligent parsing model to perform full-element structured parsing of the event form within 1 second. Based on the parsing results, it classifies the event type and determines the risk level of the event according to preset standards, forming a structured handling form with risk level.

[0031] A rigid triage logic is implemented based on the type of incident: for police incidents involving illegal activities, violent conflicts, missing persons, and risks to social stability, the system interface is used to connect synchronously with the public security police affairs platform and the police station's incident handling system; for non-police incidents involving municipal maintenance, urban management law enforcement, and market supervision, the incidents are directly transferred to the government service hotline platform with one click, and a copy is simultaneously sent to the comprehensive governance center for full-process supervision.

[0032] The system matches the corresponding differentiated response time according to the risk level of the incident, and accurately assigns the incident handling order to the corresponding responsible police officer, grid member or functional department personnel. After the order is assigned, the system continuously monitors the status of the entire incident handling process, compares the prescribed response time with the actual response time in real time, and automatically triggers the hierarchical warning and step-by-step supervision mechanism if there are any cases of overdue orders or unhandled situations.

[0033] The collaborative handling unit is used to receive event handling orders pushed by the intelligent middle platform processing unit, trigger the corresponding level of response mechanism, provide a mobile handling port for front-line handling personnel, realize cross-departmental collaborative scheduling, on-site evidence collection, real-time feedback of the handling process and automatic generation of handling reports, and simultaneously synchronize the data of the entire handling process nodes to the completion feedback unit and the early warning management unit in real time. The collaborative response unit includes a built-in dynamic dispatch submodule for response forces within the jurisdiction. Based on compliant location authorization, it constructs a real-time dynamic map of the jurisdiction's police force, grid workers, property security guards, social volunteers, and mobile grid workers. In the event of emergencies and major incidents, it automatically dispatches the response forces closest to the scene to carry out initial control, personnel rescue, and scene protection, while simultaneously transmitting the scene situation back to build a 15-minute rapid response circle. The system receives an event handling order from the intelligent middleware processing unit, reads the event type, risk level, location of the incident, and information on the responsible party, enters the handling and dispatch process, and activates the dynamic dispatch submodule of the handling forces in the jurisdiction. Under the premise of user-authorized compliant locations, it collects and updates the location information of police officers, grid workers, property security guards, social volunteers, and mobile grid workers in the jurisdiction in real time to build a dynamic force map of the entire area. The system determines the response mode based on the risk level of the incident. For emergency and major emergencies, the system automatically matches and dispatches the response force closest to the incident location according to the principle of optimal distance. It instructs the response force to arrive at the scene first to carry out initial control, personnel rescue and scene protection work. After the initial response force arrives at the scene, it transmits text, pictures, videos and location information from the scene in real time through mobile terminals. The system updates the incident situation in real time and builds a 15-minute rapid response circle covering the incident area. It also has a built-in cross-departmental collaborative handling sub-module, which automatically forms an online collaborative handling team for complex events that cross fields and departments, connects the handling personnel of the corresponding functional departments, and realizes real-time sharing of event information, synchronous updates of handling progress, and clear division of handling tasks.

[0034] For complex events that are determined to be cross-domain and cross-departmental, the cross-departmental collaborative handling submodule is activated. The system automatically filters and connects the corresponding functional departments' handling personnel based on the event type and the department's responsibility list, and establishes a special collaborative handling team online. Within the collaborative handling team, the system achieves real-time sharing of basic event information, on-site data, and handling plans, and updates the handling progress synchronously. The system automatically assigns handling tasks according to responsibilities to ensure clear division of labor and efficient collaboration.

[0035] The collaborative handling unit has a built-in AI-assisted document generation submodule, which can automatically generate standardized handling reports and work logs based on photos, videos and audio recordings collected on site, automatically complete the handling elements, and automatically archive the materials of the entire handling process to the public security police platform, grid management platform and government service platform, so as to achieve one-time entry and simultaneous retention in multiple systems. Personnel conduct on-site evidence collection, uploading multimedia materials such as photos, videos, and audio recordings. The system then activates the AI-assisted document generation submodule, which intelligently analyzes the evidence. Based on the on-site materials, the AI-assisted document generation submodule automatically extracts key information, completes the handling elements, and generates a standardized handling report and a standardized work log. No manual compilation is required. The system automatically synchronizes and archives the generated report, log, and on-site evidence materials to the public security police platform, grid management platform, and government service platform through data interfaces, achieving one-time entry and automatic retention across multiple systems. It also has a built-in blockchain evidence storage sub-module, which stores all nodes of the event handling process, operation records, evidence materials, and communication content on the blockchain to ensure that the data is tamper-proof, auditable, and traceable.

[0036] The completion feedback unit is used to receive data on the handling nodes, synchronize the progress of the entire event handling process to the public, and complete the dual verification of AI and human verification after receiving the completion application submitted by the handling personnel. After the verification is passed, the completion result and satisfaction evaluation are pushed to the public. Based on the evaluation results, the event is archived in a closed loop or the process of returning the case for re-handling is triggered. At the same time, the completed archived data is synchronized to the early warning and management unit. In the completion feedback unit, a courier-style progress tracking link is adopted. The public can view the event handling status, handling personnel, node progress, and completion time limit in real time through the original QR code entry. After each handling node is completed, progress reminders will be automatically pushed to the public via WeChat and Alipay. Receive real-time synchronized event handling process node data from the collaborative handling unit, complete the data structure organization, initialize the corresponding event's express progress tracking link, and bind the event's unique traceability code and anonymous query credentials; The system builds a dedicated progress query channel for the public based on the original QR code entry. The public can use the QR code entry for the first report, or the unique traceability code of the event or the anonymous query certificate, to view the current handling status of the event, the responsible personnel, the progress of completed nodes, and the remaining completion time in real time. For each key milestone in the handling of an incident, the system automatically triggers a progress reminder mechanism, pushing the update information to the public via WeChat and Alipay service notifications. For anonymous reports, the progress is simultaneously updated on the anonymous query interface, ensuring that the public is fully informed about the handling process. The system employs a dual verification process involving both AI and human verification. First, the AI ​​verification model performs image comparison, element verification, and matching of handling standards to assess the effectiveness of the action. If the verification fails, the case is automatically returned to the handling personnel for further processing. Once the AI ​​verification is successful, the responsible police officer or grid worker conducts a second manual review.

[0037] The system receives incident closure applications from frontline personnel, along with a complete set of closure materials including on-site photos, videos, audio recordings, closure reports, and task completion certificates, and automatically initiates a dual verification process involving both AI and human verification. The system first calls the pre-trained AI verification model to carry out the first level of intelligent verification: verifying the effectiveness of on-site rectification before and after the handling through image comparison algorithm, verifying the completeness of the handling process and the response to core demands through element verification algorithm, and verifying whether the handling process complies with the public security police and government handling norms through handling standard matching algorithm, and generating an AI verification report. If the AI ​​verification fails, the system will automatically mark the missing or unqualified items and return the case to the original personnel with one click, specifying the supplementary handling requirements and rectification deadlines; if the AI ​​verification passes, the system will automatically transfer the case to the second stage of manual review. The system will simultaneously push the completed materials and AI verification report to the corresponding responsible police officer or community grid member, who will then conduct a second manual review of the incident handling effectiveness, procedural compliance, and response to public demands to confirm whether the handling was in place, whether there were any outstanding issues, and issue a manual review opinion. In the completion feedback unit, after the double verification is passed, the completion result and star-level satisfaction evaluation portal are pushed to the public, and events with satisfactory evaluations from the public are archived in a closed loop. For incidents that elicit negative public feedback, a mechanism for returning the case for reprocessing is automatically triggered. The superior management department initiates a special supervision process until the public approves the case and the case is archived. At the same time, the completed case file is simultaneously uploaded to the corresponding government and police systems for permanent storage.

[0038] Receive satisfaction evaluations and supplementary opinions submitted by the public. For events that are rated as satisfactory by the public, formally complete the closed-loop process and generate standardized completion files from the entire process of reporting, handling, verification, and completion of the event. These files are then automatically synchronized to the public security police platform, grid management platform, and government service platform through data interfaces for permanent storage. For incidents that elicit negative public feedback, the system automatically triggers a return-for-re-handling mechanism, marking the core reasons for public dissatisfaction and returning the incident to the corresponding responsible unit for re-handling. At the same time, it sends special supervision instructions to the higher-level comprehensive governance center and police station management department, specifying the supervision requirements and rectification deadlines. After the re-handling is completed, the system restarts the dual verification process of AI and human verification, and pushes the handling results and evaluation portal to the public again until the public's evaluation is approved, thus completing the final closed-loop archiving of the incident.

[0039] The early warning and governance unit is used to receive and accumulate event data throughout the entire process, build a special database and governance profile for grassroots governance in the jurisdiction, complete the intelligent identification and hierarchical early warning of governance risks in the jurisdiction through the risk early warning model, push early warning information and prevention and control suggestions to the corresponding management entities in the jurisdiction, and at the same time complete the dynamic iterative optimization of system models and rules based on the full amount of data.

[0040] In the early warning and governance unit, standardized governance profiles can be generated for each community, grid, and building within the jurisdiction, and core indicators such as safety index, hidden danger index, conflict index, and public satisfaction index can be quantitatively output. It receives full-process, full-volume event data synchronized from the QR code reporting terminal unit, intelligent middleware processing unit, collaborative handling unit, and completion feedback unit; completes data cleaning, deduplication, classification, and standardization processing; constructs a special database for grassroots governance in the jurisdiction; and completes data collection according to the three-level governance units of community, grid, and building. For the collected three-level unit data, a unique standardized governance profile is generated for each community, each grid, and each building within the jurisdiction. Based on a preset quantitative algorithm, four core indicators are output: safety index, hidden danger index, conflict index, and public satisfaction index. These indicators accurately depict the governance status, shortcomings, weaknesses, and risk characteristics of each governance unit. The formula is as follows: ; in, The standardized scores for the corresponding indicators (safety index, hidden danger index, conflict index, and public satisfaction) This refers to the i-th basic statistical data item corresponding to the indicator, such as the safety index corresponding to the police incident rate, the hidden danger index corresponding to the number of hidden danger incidents, the conflict index corresponding to the number of reported conflicts and disputes, and the public satisfaction index corresponding to the average rating star. The weighting coefficients corresponding to the basic data are preset based on public security policing procedures and grassroots governance standards. For the standardized normalization function, k is the number of basic statistical data. The risk warning model can generate heat maps of events in the jurisdiction, spatiotemporal maps of high-incidence police incidents, and distribution maps of hidden dangers and risks based on full event data. It can accurately identify high-frequency hidden danger areas, high-incidence police incident locations, areas with frequent conflicts and disputes, and potential risks. According to the risk level, it can push warning information and rectification and prevention suggestions to the corresponding management entities. At the same time, it can provide data support for optimizing police patrol deployment, special investigation of hidden dangers, precise safety publicity, and early intervention in conflicts.

[0041] The pre-trained risk warning model is invoked, and multi-dimensional spatiotemporal analysis is conducted based on full-volume event data from the thematic database. This results in the generation of event heatmaps, spatiotemporal maps of high-incidence incidents, and distribution of potential risks within the jurisdiction. Figure 3 This visual map intuitively presents the density of events within the jurisdiction, the temporal and spatial patterns of high-incidence incidents, and the overall distribution characteristics of potential hazard locations. The formula is as follows: ; in, Let be the event heat value for the region corresponding to coordinates (x, y) during time period t. This represents the total number of events occurring within the corresponding spatiotemporal range. This represents the area coefficient for the corresponding region. The time coefficient for the statistical period. This is a function for calculating thermal values. The output results are used to generate event heatmaps, spatiotemporal maps of high-incidence incidents, and risk distribution maps. Based on the analysis results of the three types of maps and the three-level governance profile data, we can accurately identify high-frequency hidden danger areas, high-incidence police incident locations, areas with frequent conflicts and disputes, as well as potential risks and hidden dangers related to stability, danger, and fraud. According to the preset standards, the identified risks are divided into three levels: low, medium, and high, and the location, type, level, and triggering cause of each risk are clearly defined. Based on risk levels and attribution of responsibility, tiered early warning information is precisely pushed to the corresponding communities, grids, police stations, and responsible police officers, along with corresponding rectification and prevention suggestions matched to the risk type. This clarifies rectification deadlines and core prevention and control requirements, enabling early detection, early warning, and early handling of risks and hidden dangers. Furthermore, based on comprehensive data analysis and risk identification results, standardized data support is provided for various grassroots governance tasks. This includes providing precise spatiotemporal data for optimizing patrol routes and adjusting patrol times, identifying key areas and types for special investigations and rectifications of safety hazards, targeting high-risk groups and areas for anti-fraud and fire safety campaigns, and providing precise guidance for early intervention and mediation of potential conflicts and disputes. This promotes a shift in grassroots governance from passively handling complaints to proactively preventing and controlling them at the source.

[0042] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart response system for grassroots governance involving police and civilian collaboration, characterized by: It includes a QR code reporting terminal unit, an intelligent middleware processing unit, a collaborative handling unit, a completion feedback unit, and an early warning and management unit; The QR code reporting terminal unit is used to provide a standardized governance QR code entry with full coverage, which can be accessed by the public through mobile phone scanning. It automatically matches the local jurisdiction, responsible police officer and grid member corresponding to the scanned code, receives governance requests and reports submitted by the public in a multimodal manner, generates a standardized event form with a unique traceability code after completing the request pre-verification, and pushes it to the intelligent middle platform processing unit. The intelligent middleware processing unit is used to receive event orders pushed by the QR code reporting terminal unit, complete the extraction of all event elements, type classification and risk classification through the pre-trained grassroots governance event analysis model, simultaneously complete the rigid diversion of police-related and non-police-related events, complete the second-level accurate dispatch of orders according to the preset hierarchical response rules, and simultaneously push the event handling order to the collaborative handling unit of the corresponding handling entity, while synchronizing the entire process data of the event to the early warning and governance unit. The collaborative handling unit is used to receive event handling orders pushed by the intelligent middle platform processing unit, trigger the corresponding level of response mechanism, provide a mobile handling port for front-line handling personnel, realize cross-departmental collaborative scheduling, on-site evidence collection, real-time feedback of the handling process and automatic generation of handling reports, and simultaneously synchronize the data of the entire handling process nodes to the completion feedback unit and the early warning management unit in real time. The completion feedback unit is used to receive data from the handling nodes, synchronize the progress of the entire event handling process to the public, and complete the dual verification of AI and human verification after receiving the completion application submitted by the handling personnel. After the verification is passed, the completion result and satisfaction evaluation are pushed to the public. Based on the evaluation results, the event is archived in a closed loop or the process of returning the case for re-handling is triggered. At the same time, the completed archived data is synchronized to the early warning and management unit. The early warning and governance unit is used to receive and accumulate full-process event data, build a special database and governance profile for grassroots governance in the jurisdiction, complete the intelligent identification and hierarchical early warning of governance risks in the jurisdiction through the risk early warning model, push early warning information and prevention and control suggestions to the corresponding management entities in the jurisdiction, and at the same time complete the dynamic iterative optimization of system models and rules based on the full amount of data.

2. The intelligent response system for grassroots governance with police-civilian collaboration via QR code as described in claim 1, characterized in that: The standardized governance QR code of the reporting terminal unit includes a three-level structure: a general fixed code for the jurisdiction, a building-specific binding code, and a police officer's personal service code. These codes are posted on smart doorplates, unit bulletin boards, community service points, and key locations within the jurisdiction. After scanning the code, the public can directly access the service interface without downloading an app or registering and logging in. The multimodal method of submitting requests includes reporting modes that support taking photos, recording videos, speaking, and inputting text. It has a built-in intelligent recognition module for multiple local dialects and minority languages, as well as a large-character adaptation mode for the elderly. Through a multimodal big data model, it automatically extracts the event type, geographical location, involved parties, and urgency level elements from the reported content and automatically completes and generates a standardized event form.

3. The intelligent response system for grassroots governance with police-civilian collaboration via QR code as described in claim 1, characterized in that: The QR code reporting terminal unit has a built-in blockchain anonymous reporting submodule. It uses zero-knowledge proof encryption technology to encrypt the identity information of the whistleblower throughout the process. The reported event content is stored on the blockchain, which is tamper-proof and the identity of the whistleblower cannot be traced back. Only authorized personnel can view the event content. At the same time, it provides the whistleblower with an anonymous event progress query channel.

4. The intelligent response system for grassroots governance with police-civilian collaboration via QR code as described in claim 1, characterized in that: The intelligent middleware processing unit, based on a pre-built knowledge graph of grassroots governance events, a list of responsibilities of multiple departments, and training and generation of police handling standards, can complete the full-element structured analysis, event type classification, and risk classification of an event within 1 second. It also enables rigid separation of police-related and non-police-related incidents, completes precise dispatching within seconds according to preset hierarchical response rules, and automatically triggers hierarchical warnings and step-by-step supervision if the incident is not handled within the time limit.

5. The intelligent response system for grassroots governance with police-civilian collaboration via QR code as described in claim 1, characterized in that: The collaborative response unit includes a built-in dynamic dispatch submodule for response forces within the jurisdiction. Based on compliant location authorization, it constructs a real-time dynamic map of the jurisdiction's police force, grid workers, property security guards, social volunteers, and mobile grid workers. In the event of emergencies and major incidents, it automatically dispatches the response forces closest to the scene to carry out initial control, personnel rescue, and scene protection, while simultaneously transmitting the scene situation back to build a 15-minute rapid response circle. It also has a built-in cross-departmental collaborative handling sub-module, which automatically forms an online collaborative handling team for complex events that cross fields and departments, connects the handling personnel of the corresponding functional departments, and realizes real-time sharing of event information, synchronous updates of handling progress, and clear division of handling tasks.

6. The intelligent response system for grassroots governance with police-civilian collaboration via QR code as described in claim 1, characterized in that: The collaborative handling unit has a built-in AI-assisted document generation submodule, which can automatically generate standardized handling reports and work logs based on photos, videos and audio recordings collected on site, automatically complete the handling elements, and automatically archive the materials of the entire handling process to the public security police platform, grid management platform and government service platform, so as to achieve one-time entry and simultaneous retention in multiple systems. It also has a built-in blockchain evidence storage sub-module, which stores all nodes of the event handling process, operation records, evidence materials, and communication content on the blockchain to ensure that the data is tamper-proof, auditable, and traceable.

7. The intelligent response system for grassroots governance with police-civilian collaboration via QR code as described in claim 1, characterized in that: The completion feedback unit adopts a courier-style progress tracking link. The public can view the event handling status, handling personnel, node progress, and completion time limit in real time through the original QR code entry. After each handling node is completed, progress reminders will be automatically pushed to the public via WeChat and Alipay. The AI ​​and human dual verification process involves first using an AI verification model to compare images, check elements, and match handling standards to assess the effectiveness of the action. If the verification fails, the case is automatically returned to the handling personnel for further processing. Once the AI ​​verification is successful, the responsible police officer or grid worker will conduct a second manual review.

8. The intelligent response system for grassroots governance with police-civilian collaboration via QR code as described in claim 1, characterized in that: In the completion feedback unit, after the double verification is passed, the completion result and star-level satisfaction evaluation portal are pushed to the public, and events with satisfactory evaluations from the public are archived in a closed loop. For incidents that elicit negative public feedback, a mechanism for returning the case for reprocessing is automatically triggered. The superior management department initiates a special supervision process until the public approves the case and the case is archived. At the same time, the completed case file is simultaneously uploaded to the corresponding government and police systems for permanent storage.

9. The intelligent response system for grassroots governance with police-civilian collaboration via QR code as described in claim 1, characterized in that: The aforementioned early warning and governance unit can generate standardized governance profiles for each community, grid, and building within the jurisdiction, and quantitatively output core indicators such as safety index, hidden danger index, conflict index, and public satisfaction. The risk warning model can generate heat maps of events in the jurisdiction, spatiotemporal maps of high-incidence police incidents, and risk distribution maps based on full event data. It can accurately identify high-frequency hidden danger areas, high-incidence police incident locations, areas with frequent conflicts and disputes, and potential risks. According to the risk level, it can push warning information and rectification and prevention suggestions to the corresponding management entities. At the same time, it can provide data support for optimizing police patrol deployment, special investigation of hidden dangers, precise safety publicity, and early intervention in conflicts.

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