AI-powered community intelligent governance and time-series collaborative scheduling control system

Abstract

This invention discloses an AI-powered community intelligent governance and time-series collaborative scheduling control system, belonging to the fields of artificial intelligence time-series scheduling, grassroots community intelligent governance, and distributed event linkage control technology. Addressing the technical pain points of existing community governance systems—such as reliance on manual offline processing, delayed transaction response, disordered resource allocation, low efficiency of multi-departmental collaboration, and the cumbersome architecture of existing intelligent scheduling systems unable to adapt to lightweight deployment—this invention proposes a lightweight scheduling architecture of "time-series task orchestration, event-level early warning, multi-node collaborative response, and dynamic resource allocation." This system embeds a time-series task orchestration module, an event-level early warning module, a multi-node collaborative response module, and a dynamic resource allocation module; it achieves orderly transaction flow based on timestamp sorting, graded handling based on urgency level, and intelligent task dispatch based on node load. This system inherits the intelligent scheduling logic of a multi-level unit dynamic linkage collaborative control system, integrates a graded risk control mechanism, connects to a hardware security base to achieve circuit breaking for abnormal events, and connects to a responsibility anchoring and traceability system to complete the recording of handling and the tracing of responsibilities. This invention is suitable for grassroots communities, old residential areas, industrial parks, and townships, possessing the technical advantages of low power consumption, high efficiency, easy deployment, and full-process traceability.

Description

Technical Field

[0001] This invention belongs to the fields of community intelligent governance, artificial intelligence time-series scheduling, distributed collaborative control, and grassroots digital management technology, specifically involving a lightweight, highly responsive, and traceable community time-series collaborative scheduling and control system. Background Technology

[0002] Current community governance largely relies on manual registration, manual task assignment, and manual inspection, resulting in disorganized affairs, high omission rates, and delayed responses. Traditional smart platforms have cumbersome scheduling logic, consume a lot of computing power, and are unsuitable for lightweight deployment at the grassroots level. There are no clear classification standards for various events, making emergencies prone to delays. Nodes cannot coordinate, leading to chaotic resource allocation. The handling process lacks traceability, making it difficult to define responsibilities. The industry lacks a community scheduling and governance system that is suitable for grassroots communities, has low barriers to entry, is highly intelligent, time-sequential, and traceable. Summary of the Invention

[0003] This invention addresses the pain points of grassroots community governance by proposing a time-series collaborative intelligent scheduling architecture. It achieves orderly queuing of tasks through time-series task orchestration; differentiated responses through a three-level event classification system; cross-regional collaboration through multi-node linkage; and optimal resource allocation through a dynamic load balancing algorithm. This system features lightweight deployment, offline operation capability, and end-to-end encrypted traceability. It also integrates with security risk control and judicial evidence preservation modules to enable physical circuit breaking for abnormal events and permanent traceability of handling records. Beneficial effects

[0004] (1) Time-series management: tasks are automatically sorted, automatically updated, and without omission; (2) Tiered handling: Clearly distinguish between priorities, and give priority to emergency events; (3) Intelligent order dispatch: Automatically allocates orders based on load, reducing manual intervention; (4) Cross-regional collaboration: multi-node linkage and joint handling of complex events; (5) Resource optimization: Dynamically allocate manpower and materials to reduce operation and maintenance costs; (6) Full traceability: All operations are tamper-proof and used for auditing, review, and accountability. Detailed Implementation

[0005] Community daily inspections and equipment maintenance are set as periodic automatic tasks; resident repair requests and lost items are classified as general events; person falls, open fire warnings, and illegal intrusions are determined as emergency events. The system generates a task queue according to timestamps, and temporary emergencies automatically queue-jump. Regular tasks are assigned orders nearby, and busy nodes are automatically diverted. Emergency events trigger multi-node linkage at the touch of a button, and the hardware security base is synchronously called to complete area isolation and audible and visual warnings. All disposal steps, personnel operations, and time nodes generate encrypted logs, which are synchronously uploaded to the traceability and evidence preservation system for permanent retention. The system is adapted to old urban communities, rural communities, and industrial parks and can be quickly implemented at low cost.

Claims

1. An AI-powered community intelligent governance and time-series collaborative scheduling control system, characterized in that, include: The module includes a time-series task orchestration module, an event-level early warning module, a multi-node collaborative response module, and a dynamic resource allocation module. The time-series task orchestration module is used to generate task queues from daily community affairs, periodic tasks, and temporary events in a time sequence, and automatically arrange the execution order according to priority. The event classification and early warning module is used to automatically identify the types of community events and classify them into three levels: daily affairs, general events, and emergency events, corresponding to different response times and handling strategies. The multi-node collaborative response module is used to dispatch tasks to corresponding community nodes, supporting cross-node collaborative operations and synchronization of processing progress. The dynamic resource allocation module is used to monitor the resource occupancy status of each node in real time and automatically allocate manpower, equipment, and material resources according to the task load.

2. An AI-powered community intelligent governance and time-series collaborative scheduling control method, applied to the system described in claim 1, characterized in that, Includes the following steps: S1. Time-series task orchestration: Generate a task queue of community affairs according to time sequence and automatically arrange the execution order according to priority; S2. Event Classification Early Warning: Identifies event types and urgency levels, triggering corresponding early warning levels and response times; S3, Intelligent Triage and Dispatch: Based on the event type and node load, tasks are automatically dispatched to the corresponding nodes or responsible persons; S4. Cross-node collaborative processing: Supports multi-node linkage operations, real-time synchronization of processing progress, and automatic escalation if not completed within the time limit; S5. Dynamic resource allocation: Real-time monitoring of node resource usage and automatic resource allocation based on task load; S6. Full-process closed-loop traceability: The entire scheduling process generates operation logs and embeds traceability tags for post-event review and responsibility determination.

3. The system according to claim 1, characterized in that, The time-series task orchestration module supports the automatic generation of periodic tasks (such as daily inspections and weekly meetings), supports manual insertion of temporary events, and automatically rearranges the subsequent task queue.

4. The system according to claim 1, characterized in that, In the event classification and early warning module, the response time for routine matters is within 24 hours, for general events it is within 4 hours, and for emergency events it is within 30 minutes. Emergency events automatically trigger multi-node linkage response.

5. The system according to claim 1, characterized in that, The multi-node collaborative response module supports cross-node task flow, and automatically upgrades to the superior node or community governance center when a task is not completed within the time limit.

6. The system according to claim 1, characterized in that, The dynamic resource allocation module uses weighted round-robin, least connections algorithm, or other equivalent load balancing algorithms to complete task allocation based on the real-time load and historical performance data of each node.

7. The system according to claim 1, characterized in that, The system adopts a lightweight architecture design, is suitable for deployment at the edge nodes of townships, does not require a large server cluster, and can be connected to the underlying support architecture of the distributed autonomous AI digital community.

8. The system according to claim 1, characterized in that, This system inherits the intelligent scheduling layer logic of the multi-level unit dynamic linkage and collaborative control system, integrates a hierarchical risk control mechanism, connects to the hardware security base to realize circuit breaking for abnormal events, and connects to the responsibility anchoring and tracing system to complete the handling record and accountability. It works in conjunction with the distributed autonomous AI digital community full-domain underlying support architecture, resident encrypted identity confirmation and data privacy protection system to build a closed loop of distributed autonomous community governance with a full-link "scheduling-risk control-security-identity-confirmation-tracing". When an emergency event is triggered, the hardware security locking unit is linked to complete the regional risk control isolation.