Intelligent scheduling optimization method for environment disinfection in infectious disease prevention and control area

Abstract

The invention discloses an infectious disease prevention and control area environment disinfection intelligent scheduling optimization method, and relates to the technical field of disinfection and epidemic prevention, and the method comprises the following steps: receiving an operation execution completion event reported by a disinfection device, and changing the state of an associated disinfection task from execution to verification according to the event; when the disinfection task is in a to-be-verified state, executing the following operations in parallel: starting a versioned transaction log record of disinfection task operation process data, and sending a verification request to at least one external verification system to collect independent verification evidence; calling a rule engine module based on a preset disinfection strategy version, judging the process data in the versioned transaction log and the received independent verification evidence, and generating a verification conclusion; according to the verification conclusion, the final state of the disinfection task is updated, and an evidence packet containing the versioned transaction log, the independent verification evidence and the verification conclusion is triggered to be archived; the problem that the prior art lacks a tracing basis is solved.

Description

Technical Field

[0001] This invention relates to the field of disinfection and epidemic prevention technology, specifically to an intelligent scheduling and optimization method for environmental disinfection in infectious disease control areas. Background Technology

[0002] Existing infectious disease control and prevention regional environmental disinfection scheduling systems typically employ linear state flow management of task execution processes and often use intelligent disinfection vehicles as the main disinfection equipment. After receiving a task, the intelligent disinfection vehicle enters the execution state, completes the spraying operation, and reports a task completion signal. The scheduling system then automatically updates the task status to completed.

[0003] However, when the intelligent disinfection vehicle reports the end of the spraying action, the scheduling system directly updates the task status from "in execution" to "completed". This design makes it impossible for the system to forcibly collect and verify the key process parameters that determine the disinfection effect. At the same time, it lacks a third-party verification mechanism independent of the execution unit. When environmental sampling re-examination shows a positive result, the system cannot trace the situation at any time. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an intelligent scheduling and optimization method for environmental disinfection in infectious disease control areas.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides an intelligent scheduling and optimization method for environmental disinfection in infectious disease control areas, comprising the following steps: Receive the operation completion event reported by the disinfection equipment, and change the status of the associated disinfection task from "in execution" to "pending verification" based on the event; While the disinfection task is in the pending verification state, the following operations are performed in parallel: initiate versioned transaction logging of the disinfection task operation process data, and send a verification request to at least one external verification system to collect independent verification evidence; Based on the preset disinfection strategy version, the rule engine module is invoked to perform consistency verification and effect compliance determination on the process data in the versioned transaction log and the received independent verification evidence, and generate verification conclusions. Based on the verification conclusion, update the final state of the disinfection task and trigger the archiving of the evidence package containing the versioned transaction log, the independent verification evidence, and the verification conclusion.

[0006] As a preferred embodiment of the present invention, forcibly changing the status of the associated disinfection task from "in execution" to "pending verification" based on the event includes: Intercept the event indicating that the job has been completed; Based on the task identifier carried in the event, the status field of the corresponding task in the scheduling system is modified to pending verification to prevent the task from directly entering the completed state.

[0007] As a preferred embodiment of the present invention, the initiation of versioned transaction log recording includes: Create a dedicated transaction log stream for the disinfection task; Record the original sensor data packets and internal system state change events reported by the disinfection equipment in chronological order, using an append-only method. Each log record contains a timestamp, a hash value of the data content, and a source signature, and the records form a chain structure through hash references.

[0008] As a preferred embodiment of the present invention, sending a verification request to at least one external verification system includes: Send a process data integrity check request to the disinfection effectiveness digital archive; Send an environmental sampling verification request to a third-party environmental sampling unit, the request including at least the sampling location coordinates determined based on the trajectory of the disinfection vehicle.

[0009] As a preferred technical solution of the present invention, the step of calling the rule engine module for consistency verification and effect compliance determination includes: According to the disinfection strategy version, load the corresponding verification rule set, which includes process parameter compliance rules and multi-source evidence consistency rules. Extract structured data fragments from the versioned transaction log; The verification rule set is executed, the satisfaction level of each rule is calculated, and the independent verification evidence is compared to generate a judgment report containing the overall conclusion and the satisfaction level of each item.

[0010] As a preferred embodiment of the present invention, the method further includes: If the verification conclusion is unsuccessful, the tendency to enforce liability will be pre-judged based on the unmet rule types and evidentiary contradictions in the judgment report. The results of the liability tendency prediction include at least one of the following: abnormal execution process, abnormal data credibility, or abnormal strategy adaptability.

[0011] As a preferred embodiment of the present invention, the method further includes: Set up an asynchronous callback and timeout mechanism for the verification request sent to the external verification system; If no valid feedback is received from all external verification systems within the preset total timeout period, the rule engine module is triggered to make a mandatory judgment based on the collected evidence.

[0012] As a preferred embodiment of the present invention, the triggering of archiving the evidence package includes: The final hash chain of the versioned transaction log, the judgment report generated by the rule engine module, and the feedback results from various external verification systems are packaged together to form the evidence package; The evidence package is stored in a digital archive of disinfection effects, and a multi-dimensional index based on task identification and verification status is established.

[0013] The present invention also provides an electronic device, including a memory and one or more programs, wherein one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs including a method for intelligent scheduling and optimization of environmental disinfection in infectious disease prevention and control areas.

[0014] The present invention also provides a readable storage medium, wherein when the instructions in the storage medium are executed by the processor of an electronic device, the electronic device is able to execute an intelligent scheduling optimization method for disinfection of the infectious disease prevention and control area.

[0015] The beneficial effects of this invention are: This invention effectively solves the problem of missing verification caused by the direct jump of the task status to completed in the prior art after the intelligent disinfection vehicle reports the completion of the operation. In the pending verification state, versioned transaction log recording and external verification requests are executed in parallel to ensure that key process parameters such as disinfectant concentration, spray coverage uniformity, and contact time are completely collected and cannot be tampered with. At the same time, the invention introduces independent verification evidence from the disinfection effect digital archive and third-party environmental sampling units, which changes the single self-reporting mechanism and provides multi-dimensional data support for disinfection effect verification, so that the task status update has objective basis rather than subjective judgment. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0017] Figure 1 This is a schematic diagram illustrating the workflow of the intelligent scheduling and optimization method for infectious disease prevention and control area environmental disinfection according to the present invention. Detailed Implementation

[0018] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0019] like Figure 1As shown, the intelligent scheduling and optimization method for environmental disinfection in infectious disease control areas includes the following steps: The system receives a completion event reported by disinfection equipment (such as an intelligent disinfection vehicle) and changes the status of the associated disinfection task from "in execution" to "pending verification" based on the event. This forcibly inserts an unskippable intermediate step between the two traditional states of "in execution" and "completed," thereby blocking the direct triggering of task completion by the completion event at the business logic level and creating a necessary process window for subsequent multi-source evidence collection and judgment.

[0020] While the disinfection task is in the pending verification state, the following operations are performed in parallel: initiate versioned transaction logging of the disinfection task operation process data, and send a verification request to at least one external verification system to collect independent verification evidence; Versioned transaction logs are data record structures organized in chronological order and in an append-only manner. They are usually set up as a separate log service or stored in a dedicated table in a database. Their purpose is to ensure that a single disinfection task is immutable and traceable throughout the entire process, and to ensure the integrity, continuity and reliability of all operational process data (such as sensor readings) and system state change events. External verification systems refer to external business entities or services that are independent of the intelligent disinfection vehicle and the core scheduling program. Typical examples include a digital archive of disinfection effects and a third-party environmental sampling unit. The purpose of introducing these external verification systems is to break the reliance on the self-reporting of disinfection equipment (such as intelligent disinfection vehicles) and to provide objective and neutral verification evidence through independent verification parties (archives) and verification parties (sampling units), thereby forming a multi-party evidence chain that can corroborate each other.

[0021] Based on the preset disinfection strategy version, the rule engine module is invoked to perform consistency verification and effect compliance determination on the process data in the versioned transaction log and the received independent verification evidence, and generate verification conclusions. The rules engine module is a software component that encapsulates business judgment logic. It is used to load and execute predefined "verification rule sets". Its purpose is to decouple the disinfection effect standards (such as concentration, time, and coverage requirements) and evidence consistency rules (such as the logic of comparing process data with sampling results) set by business personnel from the program code, so as to realize declarative, configurable, automated comprehensive judgment and make a preliminary judgment on the tendency of responsibility based on the rule execution results.

[0022] Based on the verification conclusion, update the final state of the disinfection task and trigger the archiving of the evidence package containing the versioned transaction log, the independent verification evidence, and the verification conclusion to complete the business loop; An evidence package is a structured collection of data designed to standardize, encapsulate, and archive all evidence materials related to the current task that are scattered across transaction logs, rule engine reports, and various external verification systems, forming a complete business file unit that can be independently audited, facilitates long-term traceability, and is subject to compliance review.

[0023] The specific workflow is as follows: First, when the system receives the operation completion event reported by the intelligent disinfection vehicle, the event becomes the trigger point for the entire mandatory verification process. The system will immediately change the status of the corresponding task from "in execution" to "pending verification" according to the task identifier carried in the event. This status change operation is mandatory in business, which means that the task is locked and cannot be directly marked as completed through the regular process.

[0024] Following this, while the task is in the verification phase, the system will initiate two key operations in parallel. The first operation is to start versioned transaction logging, which means that the raw sensor data packets (such as concentration and pressure values) continuously reported by the disinfection vehicle, as well as all subsequent state change events within the system, will be recorded in a dedicated log stream in chronological order and immutably. The second operation is to send a verification request to at least one external verification system. For example, it may simultaneously request the disinfection effect digital archive to perform an integrity check on the process data to be added to the archive, and request a third-party environmental sampling unit to go to the disinfection area to collect environmental samples to obtain biological verification evidence. These two operations are parallel and independent evidence collection processes.

[0025] Then, the system will call the rule engine module to make a judgment based on the preset disinfection strategy version. Specifically, the rule engine module will load the verification rule set corresponding to the strategy version. It does not directly process the raw data stream, but extracts structured process data fragments from the recorded versioned transaction logs. At the same time, it waits for or obtains independent verification evidence from external verification systems (such as integrity feedback from the archive and detection results from sampling units). Based on the preset rules, the engine performs consistency verification and effect compliance judgment on these multi-source data, and finally generates a verification conclusion (pass or fail) and a detailed judgment report.

[0026] Finally, based on the verification conclusion, the system updates the final state of the task and triggers the archiving of the evidence package. If the conclusion is passed, the task status is officially updated from "pending verification" to "completed"; if it fails, it is updated to a final state such as "verification failed". Regardless of the final state, the system will automatically trigger the archiving process: the final copy of the versioned transaction log of this task, the judgment report generated by the rule engine module, and the feedback results of all external verification systems are packaged into a complete evidence package and stored in the disinfection effect digital archive, thereby completing the complete business loop of this disinfection task from execution to verification to archiving.

[0027] Furthermore, forcibly changing the status of the associated disinfection task from "in execution" to "pending verification" based on the event includes: The event of the completed operation is intercepted. The event message body contains structured data such as task identifier, vehicle number, start and end timestamps of the operation, and basic spraying parameters. Upon receiving the event, the event interception operation is first performed, that is, the event is prevented from being forwarded directly to the task dispatch and acceptance trigger according to the linear processing path of the traditional system. This interception mechanism is the starting point of business logic reconstruction, ensuring that the subsequent mandatory verification process cannot be bypassed.

[0028] Based on the task identifier carried in the event, the status field of the corresponding task in the scheduling system is modified to pending verification in order to prevent the task from directly entering the completed state. After successfully intercepting the job completion event, the corresponding disinfection task entity in the scheduling system is immediately retrieved based on the task identifier carried in the event. This task identifier serves as a unique index, ensuring the accuracy and relevance of the state change operation. Subsequently, a forced modification operation is performed on the state field of the task entity, changing the task status from "in execution" to "pending verification." This state transition has an irreversible unidirectional characteristic, meaning that the task cannot enter the completed state through any path before receiving a verification pass instruction. This forced state locking mechanism establishes an ironclad rule of "no completion without verification" at the business level, effectively blocking state transition vulnerabilities caused by single event triggers in traditional systems.

[0029] In practical applications, this forced status change mechanism can effectively prevent misjudgment of task status due to false reports from disinfection vehicles, communication abnormalities, or system failures. For example, when an intelligent disinfection vehicle reports the completion of its operation ahead of schedule due to sensor failure, the task status will still be changed to pending verification. However, since the rule engine cannot obtain complete process parameter data, the task will fail verification, thus avoiding the situation where incomplete disinfection operations are incorrectly marked as completed.

[0030] This design fundamentally eliminates the business logic gap between the execution process and the effect verification, providing a solid technical foundation for building a verifiable and traceable closed loop for disinfection tasks.

[0031] Furthermore, the startup versioned transaction log recording includes: Create a dedicated transaction log stream for the disinfection task; The transaction log stream has a globally unique log sequence number, which corresponds one-to-one with the task identifier. This ensures that the log records of different disinfection tasks are completely isolated at the physical storage and logical processing levels, avoiding data confusion. This dedicated log stream design mechanism enables each disinfection task to have an independent and complete operation trajectory record, providing a clear data boundary for the subsequent construction of the evidence chain.

[0032] Record the original sensor data packets and internal system state change events reported by the disinfection equipment in chronological order, using an append-only method. After creating a dedicated transaction log stream, all critical operation data are recorded in strict chronological order using atomic operations.

[0033] The recorded content mainly includes two categories: the first category is the raw sensor data packets reported by the intelligent disinfection vehicle, including key process parameters that determine the disinfection effect, such as real-time readings of disinfectant concentration, nozzle pressure values, movement speed vectors, and GPS coordinate sequences; the second category is system internal state change events, including system-level operation traces such as state machine transition records, rule engine judgment results, and verification request responses.

[0034] All logging operations use an append-only mode, meaning that once a log record is written to the storage medium, it cannot be modified or deleted. This design fundamentally guarantees the integrity and originality of log data.

[0035] At the data structure level of log records, each log record contains three core elements: a timestamp accurate to milliseconds, a hash value of the data content, and a source signature.

[0036] Timestamps ensure the temporal accuracy of the operation sequence and provide a time reference for subsequent causal analysis; the hash value of the data content is generated using the SHA-256 algorithm to verify the integrity of the data during transmission and storage. Source signatures are divided into two categories based on the data source: For raw sensor data from intelligent disinfection vehicles, device digital signatures are used for identity authentication; For operation records generated internally by the system, the source is identified using a system service signature.

[0037] This three-element structure design ensures that each log record has verifiable identity attributes and integrity guarantees.

[0038] More importantly, the log records form a chain structure through hash references.

[0039] The specific implementation method is as follows: each newly written log record contains not only the hash value of its own data content, but also the complete hash value of the previous log record.

[0040] This chained referencing mechanism makes the entire transaction log stream form an immutable hash chain. Any tampering with historical log records will cause the hash chain of all subsequent log records to break, and thus be detected immediately by the system.

[0041] In practical applications, when the rule engine module needs to extract data from the versioned transaction log for verification, it first performs integrity verification on the hash chain of the entire log stream. Only log data that passes the verification will be used for subsequent judgment calculations.

[0042] Furthermore, sending a verification request to at least one external verification system includes: Send a process data integrity check request to the disinfection effectiveness digital archive; Specifically, the verification process begins by sending a process data integrity check request to the disinfection effectiveness digital archive.

[0043] The core purpose of this request is to require the disinfection effectiveness digital archive to pre-verify the data to be stored, ensuring that the original or derived data, including core parameters that determine the disinfection effect such as disinfectant concentration, spray coverage uniformity, and effective contact time, are complete and available.

[0044] Upon receiving the request, the disinfection effect digital archive will shift from passively receiving data to actively verifying it. It will reserve storage space in advance, prepare data receiving interfaces, and perform real-time checks on the integrity of data fields, especially verifying the integrity of key parameters required by the rule engine.

[0045] This process data integrity check mechanism ensures that the subsequent rule engine can obtain a complete and reliable data foundation when making parameter compliance judgments, avoiding misjudgments caused by missing data.

[0046] At the same time, an environmental sampling verification request is sent to a third-party environmental sampling unit. This request is transmitted through a standardized API interface and contains multiple key parameter information, including at least the sampling location coordinates determined based on the trajectory of the disinfection vehicle.

[0047] These sampling location coordinates are not randomly selected, but are key points identified by algorithms based on the GPS trajectory data reported by the intelligent disinfection vehicle during the task. These include high-risk locations such as the start and end points of the work path, turning points, and areas where the vehicle stays for a long time. In addition, the environmental sampling verification request also includes auxiliary information such as a suggested sampling time window (usually within a specific time period after the disinfection operation is completed to ensure the timeliness of the test results) and the task urgency level (used to guide the priority scheduling of sampling units). After receiving the request, the third-party environmental sampling unit will automatically generate a sampling task work order. Its task management system and disinfection scheduling system are synchronized through an event bus to ensure that the sampling operation can be executed in a timely and accurate manner.

[0048] Regarding the request processing mechanism, an asynchronous callback and timeout mechanism is adopted. After issuing a verification request, instead of waiting for an immediate response, an independent timeout timer is set for each verification request.

[0049] This design takes into full account the response characteristics of different verification systems: the data integrity check of the disinfection effect digital archive can usually be completed in a short time, while the environmental sampling verification of the third-party environmental sampling unit requires multiple steps such as on-site sampling and laboratory testing, which takes a long time.

[0050] Through the asynchronous mechanism, the system can continue to process other tasks while waiting for verification results, improving overall operating efficiency. When any verification request times out, the system will perform corresponding timeout processing according to the preset strategy to ensure that the task will not be stalled indefinitely.

[0051] Furthermore, the process of calling the rule engine module for consistency verification and effect compliance determination includes: According to the disinfection strategy version, load the corresponding verification rule set, which includes process parameter compliance rules and multi-source evidence consistency rules. Calling the rule engine module for consistency verification and effect compliance determination first involves loading the corresponding verification rule set according to the disinfection strategy version. The rule engine module obtains the strategy version number associated with the current disinfection task from the disinfection effect digital archive and loads the complete verification rule set corresponding to that version.

[0052] This set of verification rules strictly includes two core categories of rules: process parameter compliance rules and multi-source evidence consistency rules.

[0053] The process parameter compliance rules are used to assess whether key parameters during the disinfection process meet the preset standards, including the proportion of time the disinfectant concentration remains at the standard, the estimated value of the spray coverage uniformity, and the estimated effective contact time. The multi-source evidence consistency rule is used to verify whether there are contradictions between evidence from different sources, ensuring data credibility and result reliability.

[0054] The rule set is defined in a declarative manner, with a clear logical structure and configurability, which can adapt to the judgment requirements of different disinfection scenarios, while ensuring the version consistency and traceability of the judgment criteria.

[0055] Extract structured data fragments from the versioned transaction log; It is important to clarify that the rules engine does not directly process the raw sensor data stream, but makes judgments based on the structured data in the versioned transaction log that has already undergone hash verification and time alignment.

[0056] This design ensures the reliability and time-series accuracy of the data source, avoiding the risks of transmission delays, data loss, or tampering that may exist in real-time data streams. The extracted structured data fragments include key process parameters such as disinfectant concentration time series data, spray pressure change curves, movement speed vectors, and GPS trajectory coordinates, as well as auxiliary information such as system internal state change records and verification request responses. All data fragments contain accurate timestamps and data integrity identifiers, providing a reliable data foundation for subsequent rule execution.

[0057] The verification rule set is executed, the satisfaction level of each rule is calculated, and the independent verification evidence is compared to generate a judgment report containing the overall conclusion and the satisfaction level of each item. Rule execution employs a multi-layered verification logic: the first layer performs data integrity verification, checking whether the transaction log contains all the data fields required by the rule and whether the time series is continuous; The second layer performs parameter compliance verification by substituting the extracted data fragments into the rule expression to calculate the percentage of satisfaction for each parameter. The third layer performs multi-source consistency verification, comparing the rule calculation results with the collected independent verification evidence, including data integrity feedback from the disinfection effect digital archive and sampling results from third-party environmental sampling units.

[0058] The rule engine internally maintains a confidence scoring model. When multiple sources of evidence point to consistency, the confidence level is increased; when contradictions arise, the confidence level is decreased and the contradictions are marked. The final judgment report adopts a structured format, including the overall conclusion (pass / fail) and the satisfaction level of each item (the specific percentage of compliance for each rule, data integrity score, consistency score, etc.), providing an objective basis for task status transitions and responsibility delineation.

[0059] It should be noted that the step of calling the rule engine module for judgment is triggered when any of the following conditions are met: The duration of the sensor data stream stoppage detected by the intelligent disinfection vehicle exceeded a threshold. Receive confirmation responses from all external verification systems for the verification requests; Received a mandatory judgment command initiated by the system administrator.

[0060] The first condition is that after the disinfection vehicle completes its on-site work, its sensor data stream will gradually stop. The system sets a preset threshold for the quiet time after the work ends (usually 5-10 minutes). When the data stream stops for more than this threshold, it indicates that the physical work has been substantially completed. At this time, the rule engine is triggered to make a judgment, which can ensure that the disinfection task is completed in a timely manner. In practical application scenarios, this condition is applicable to most standard disinfection operation scenarios. It can automatically identify the work completion status and avoid process blockage caused by communication delays or abnormal data reporting by the disinfection vehicle.

[0061] The second condition is that after sending verification requests to the disinfection effect digital archive and the third-party environmental sampling unit, the system will wait for these two external verification systems to return confirmation that the request has been received, rather than waiting for the final verification result. This design separates the confirmation of request receipt from the feedback of the final result, ensuring that the rule engine can intervene in a timely manner after the external verification process is started, to make a preliminary judgment or prepare for subsequent judgments. In emergency scenarios of infectious disease prevention and control, such as terminal disinfection tasks at epidemic sites, this condition allows the system to make a preliminary assessment based on the integrity of process data before the sampling unit returns the final test results, providing timely support for emergency decision-making, while not delaying the entire scheduling process due to slow response from external systems.

[0062] The third condition is receiving a mandatory judgment command initiated by the system administrator. This condition is a manual intervention channel. When the system's automatic triggering condition fails or encounters special circumstances, authorized system administrators can manually trigger the mandatory judgment command through the management interface. In major epidemic prevention and control scenarios, when the disinfection task in a key area is suspended for a long time due to the failure of the external verification system, the administrator can make a mandatory judgment based on existing evidence to ensure that the scheduling resources can be released in a timely manner for other emergency tasks. The design of this condition reflects the system's balance between automation and manual control, maintaining the rigor of the process while having the flexibility to deal with abnormal situations.

[0063] In actual operation, the system monitors the status of these three conditions in real time. Once any condition is met, the rule engine module is immediately activated to load the corresponding verification rule set and begin to comprehensively analyze the process data in the versioned transaction log and the collected independent verification evidence to generate an objective verification conclusion.

[0064] Furthermore, the method also includes: If the verification conclusion is unsuccessful, the tendency to enforce liability will be pre-judged based on the unmet rule types and evidentiary contradictions in the judgment report. These rule types mainly include various indicators in the process parameter compliance rules (such as insufficient disinfectant concentration compliance time ratio, non-compliance of coverage uniformity estimation value, insufficient estimation of effective contact time, etc.) and verification failure items in the multi-source evidence consistency rules (such as transaction log hash verification failure, abnormal data integrity feedback, contradiction between sampling results and process parameters, etc.).

[0065] Meanwhile, the module analyzes points of contradiction in the evidence, namely inconsistencies between different sources of evidence, such as differences between transaction log records and external verification feedback, and contradictions between the compliance of process parameters and actual sampling results. This in-depth analysis based on the judgment report ensures that the prediction of liability tendencies has clear data support and logical basis.

[0066] The results of liability tendency prediction strictly include at least one of three types: abnormal execution process, abnormal data credibility, or abnormal strategy adaptability.

[0067] Abnormalities in the execution process mainly refer to the failure of the disinfection vehicle to meet the preset standards during actual operation. Typical manifestations include the failure to meet key indicators in the process parameter compliance rules, such as the disinfectant concentration being consistently lower than the threshold, uneven spray coverage, or insufficient effective contact time. Data credibility anomalies mainly refer to reliability issues in the data collection, transmission, or storage process. Typical manifestations include transaction log hash verification failures, significant missing or contradictory sensor data, and data integrity scores below the threshold. Strategy mismatch mainly refers to the mismatch between the disinfection strategy itself and specific environmental conditions. A typical manifestation is that all process parameters meet the standards, but the third-party sampling results are still positive.

[0068] These three liability orientations cover the main reasons for the failure of disinfection tasks, providing a clear direction for subsequent problem handling.

[0069] In practical applications of infectious disease prevention and control, this responsibility tendency prediction mechanism has significant technical value. When environmental sampling re-examination yields positive results, the system can quickly locate the root cause of the problem through responsibility tendency prediction without the need for manual analysis.

[0070] For example, if the execution process is determined to be abnormal, maintenance personnel can focus on checking the equipment status and operating procedures of the intelligent disinfection vehicle; if the data reliability is determined to be abnormal, technicians can prioritize checking sensor failures or communication problems; if the strategy adaptability is determined to be abnormal, it will prompt that the applicability of the current disinfection strategy in the specific environment needs to be reassessed.

[0071] Furthermore, the method also includes: Set up an asynchronous callback and timeout mechanism for the verification request sent to the external verification system; After sending a process data integrity check request to the disinfection effect digital archive and an environmental sampling verification request to the third-party environmental sampling unit, the corresponding callback function is immediately registered and an independent timeout timer is started.

[0072] Each timeout timer has a different timeout threshold set according to the type and urgency of the verification request. For example, the timeout threshold for process data integrity check requests can be set to 30 minutes, while the timeout threshold for environmental sampling verification requests can be set to 24 hours.

[0073] During the timing period, the system does not block the execution of other tasks, but continues to process other disinfection tasks or system operations. When the external verification system returns a response, the response data is processed asynchronously through a pre-registered callback function.

[0074] If no valid feedback is received from all external verification systems within the preset total timeout period, the rule engine module is triggered to make a mandatory judgment based on the collected evidence. The preset total timeout is a system-level parameter, usually set to the maximum value among all individual verification request timeout thresholds, such as 48 hours.

[0075] When the total timeout period expires, a timeout notification event is sent to the rule engine module, which then initiates the mandatory judgment process.

[0076] In the mandatory determination, the rule engine module only performs a comprehensive analysis based on the collected valid evidence, including process data in the versioned transaction log and returned external verification feedback, and adopts a conservative evaluation strategy for missing verification evidence.

[0077] For example, if the environmental sampling verification request times out and does not return, it is considered a sampling failure in the multi-source evidence consistency verification, and the confidence score is adjusted accordingly. The verification conclusion generated by the forced judgment will be clearly marked with a forced judgment timeout flag to remind the system administrator that the conclusion is based on an incomplete chain of evidence.

[0078] For example, during the emergency response phase of a sudden outbreak, the terminal disinfection task at an epidemic site needs to be verified and closed quickly. However, the third-party environmental sampling unit cannot return the sampling results within the standard time due to task backlog. In this case, the timeout enforcement mechanism can generate a preliminary verification conclusion based on the existing process parameter compliance data and transaction log integrity evidence, ensuring that the scheduling system can release resources in a timely manner to handle new emergency tasks. At the same time, the system will mark the task as requiring subsequent verification. When the sampling results are finally returned, the re-verification process can be triggered to update the final conclusion.

[0079] Furthermore, the triggering of archiving the evidence package includes: The final hash chain of the versioned transaction log, the judgment report generated by the rule engine module, and the feedback results from various external verification systems are packaged together to form the evidence package; The final hash chain of the versioned transaction log represents the integrity proof of all operation records during the entire disinfection task execution process. This hash chain is generated using the SHA-256 algorithm to ensure that any tampering with the historical log will result in a change in the hash value, which will then be detected by the system.

[0080] The judgment report generated by the rules engine module contains key information such as the overall verification conclusion, details of the satisfaction of individual rules, data integrity assessment, and multi-source consistency score, which is the authoritative basis for judging the task effect.

[0081] Feedback from various external verification systems includes independent verification evidence such as the process data integrity check results of the disinfection effect digital archive and the sampling verification results of the third-party environmental sampling unit. These three types of core evidence materials are packaged together through a standardized data encapsulation protocol to form a unified and complete evidence package. Each evidence package contains metadata header information, identifying basic attributes such as task ID, disinfection vehicle number, operation time range, and verification status.

[0082] The evidence package is stored in a digital archive of disinfection effects, and a multi-dimensional index based on task identification and verification status is established. The disinfection effect digital archive adopts an immutable storage mechanism to ensure that once the evidence package is written, it cannot be modified or deleted. All storage operations are recorded in the audit log. The establishment of multi-dimensional indexes is a key link in evidence package management. The index dimensions are strictly designed based on task identifiers (such as task ID, disinfection vehicle number, and operation time range) and verification status (such as completed, verification failed - execution process abnormal, verification failed - data credibility abnormal, verification failed - strategy adaptability abnormal).

[0083] This multi-dimensional indexing mechanism supports efficient evidence retrieval and analysis. For example, it can quickly query the task evidence package of all strategy adaptation anomalies within a certain time period, or query all task history records executed by a specific disinfection vehicle. In the actual application scenario of infectious disease prevention and control, when a positive sample reappears in a certain area, epidemic prevention personnel can use this indexing mechanism to quickly locate the complete evidence package of the relevant disinfection tasks and analyze the root cause of the prevention and control failure.

[0084] Each evidence package, as an independent business unit, contains end-to-end data from task creation to finalization. Other modules of the scheduling system can only query the final status and cannot bypass the verification center to directly modify the archived evidence content. This design ensures the integrity and credibility of the evidence chain.

[0085] Furthermore, the present invention also provides an electronic device, including a memory and one or more programs, wherein one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs including a method for intelligent scheduling and optimization of environmental disinfection in infectious disease prevention and control areas.

[0086] The memory, as the data storage unit of the electronic device, is constructed using non-volatile storage media to persistently store all program code and configuration data required for system operation. The processor executes multiple processing steps of the method in parallel through a multi-threaded scheduling mechanism. In particular, it can simultaneously handle parallel operations such as transaction log recording, external verification request distribution, and rule engine judgment. The processor is equipped with a dedicated cryptographic coprocessor for efficiently calculating the hash chain value of the transaction log and verifying digital signatures, ensuring the real-time nature of data integrity verification.

[0087] In practical applications of infectious disease prevention and control, this electronic device is usually deployed in a server cluster in the dispatch center. One processor is responsible for the real-time verification of high-priority terminal disinfection tasks at epidemic sites, while another processor is responsible for the batch processing of preventive disinfection tasks. The optimal allocation of resources is achieved through a load balancing mechanism.

[0088] Furthermore, the present invention also provides a readable storage medium, wherein when the instructions in the storage medium are executed by the processor of an electronic device, the electronic device is able to execute an intelligent scheduling optimization method for disinfection of the infectious disease prevention and control area.

[0089] The readable storage medium is implemented using non-volatile storage technology, including but not limited to solid-state drives, flash memory chips, optical discs, or cloud storage services. When the processor loads and executes the instructions in the storage medium, the system can automatically construct a closed-loop evidence chain mandatory verification hub, realizing fully automated processing from task status takeover to evidence archiving. When the processor executes these instructions, it first initializes the system operating environment and establishes communication connections with the intelligent disinfection vehicle, the disinfection effect digital archive, and the third-party environmental sampling unit; then it enters the event listening state, receives the job completion event in real time, and triggers the subsequent verification process; during the verification process, the processor executes transaction log recording and verification request distribution in parallel according to the instruction requirements, and coordinates the collection work of multiple evidence sources; when the rule engine triggering conditions are met, the processor loads the corresponding verification rule set and performs multi-dimensional judgment based on the trusted data in the versioned transaction log; finally, it updates the task status according to the verification conclusion and archives the complete evidence package to the disinfection effect digital archive.

[0090] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent scheduling and optimization of environmental disinfection in infectious disease control areas, characterized in that, Includes the following steps: Receive the operation completion event reported by the disinfection equipment, and change the status of the associated disinfection task from "in execution" to "pending verification" based on the event; While the disinfection task is in the pending verification state, the following operations are performed in parallel: initiate versioned transaction logging of the disinfection task operation process data, and send a verification request to at least one external verification system to collect independent verification evidence; Based on the preset disinfection strategy version, the rule engine module is invoked to perform consistency verification and effect compliance determination on the process data in the versioned transaction log and the received independent verification evidence, and generate verification conclusions. Based on the verification conclusion, update the final state of the disinfection task and trigger the archiving of the evidence package containing the versioned transaction log, the independent verification evidence, and the verification conclusion.

2. The intelligent scheduling and optimization method for environmental disinfection in infectious disease prevention and control areas according to claim 1, characterized in that, The event will be used to forcibly change the status of the associated disinfection task from "in execution" to "pending verification," including: Intercept the event indicating that the job has been completed; Based on the task identifier carried in the event, the status field of the corresponding task in the scheduling system is modified to pending verification to prevent the task from directly entering the completed state.

3. The intelligent scheduling and optimization method for environmental disinfection in infectious disease prevention and control areas according to claim 2, characterized in that, The startup versioned transaction log records include: Create a dedicated transaction log stream for the disinfection task; Record the original sensor data packets and internal system state change events reported by the disinfection equipment in chronological order, using an append-only method. Each log record contains a timestamp, a hash value of the data content, and a source signature, and the records form a chain structure through hash references.

4. The intelligent scheduling and optimization method for environmental disinfection in infectious disease prevention and control areas according to claim 1, characterized in that, Sending a verification request to at least one external verification system includes: Send a process data integrity check request to the disinfection effectiveness digital archive; Send an environmental sampling verification request to a third-party environmental sampling unit, the request including at least the sampling location coordinates determined based on the trajectory of the disinfection vehicle.

5. The intelligent scheduling and optimization method for environmental disinfection in infectious disease prevention and control areas according to claim 1, characterized in that, The consistency verification and performance evaluation performed by the rule engine module include: According to the disinfection strategy version, load the corresponding verification rule set, which includes process parameter compliance rules and multi-source evidence consistency rules. Extract structured data fragments from the versioned transaction log; The verification rule set is executed, the satisfaction level of each rule is calculated, and the independent verification evidence is compared to generate a judgment report containing the overall conclusion and the satisfaction level of each item.

6. The intelligent scheduling and optimization method for environmental disinfection in infectious disease prevention and control areas according to claim 5, characterized in that, The method further includes: If the verification conclusion is unsuccessful, the tendency to enforce liability will be pre-judged based on the unmet rule types and evidentiary contradictions in the judgment report. The results of the liability tendency prediction include at least one of the following: abnormal execution process, abnormal data credibility, or abnormal strategy adaptability.

7. The intelligent scheduling and optimization method for environmental disinfection in infectious disease prevention and control areas according to claim 4, characterized in that, The method further includes: Set up an asynchronous callback and timeout mechanism for the verification request sent to the external verification system; If no valid feedback is received from all external verification systems within the preset total timeout period, the rule engine module is triggered to make a mandatory judgment based on the collected evidence.

8. The intelligent scheduling and optimization method for environmental disinfection in infectious disease prevention and control areas according to claim 1, characterized in that, The triggering of archiving the evidence package includes: The final hash chain of the versioned transaction log, the judgment report generated by the rule engine module, and the feedback results from various external verification systems are packaged together to form the evidence package; The evidence package is stored in a digital archive of disinfection effects, and a multi-dimensional index based on task identification and verification status is established.

9. An electronic device, characterized in that, It includes a memory and one or more programs, wherein one or more programs are stored in the memory and configured to be executed by one or more processors. The one or more programs include a method for performing intelligent scheduling optimization of infectious disease prevention and control area environmental disinfection as described in any one of claims 1-8.

10. A readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is able to execute the intelligent scheduling optimization method for disinfection of infectious disease prevention and control areas as described in any one of claims 1-8.

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