A landscaping maintenance monitoring and early warning method and system

Abstract

The application discloses a kind of garden greening maintenance monitoring early warning method and system, belong to maintenance management technical field.The method includes the following steps: establish risk event and maintenance behavior association record;According to risk state change information, divide risk event stage, establish risk evolution record;Generate initial risk early warning result and expected risk change process;Actual risk state change process is compared with expected risk change process, determine change deviation;Analysis maintenance behavior mechanism, establish maintenance behavior influence relationship record;Revision the initial risk early warning result, form updated risk early warning record.The application establishes risk event and maintenance behavior association record, combines risk evolution process analysis actual maintenance response deviation, and dynamically revises risk early warning result according to maintenance behavior influence relationship, solves the problem that risk early warning result and maintenance execution feedback association are insufficient in prior art, leading to poor adaptability of early warning adjustment.

Description

Technical Field

[0001] This application relates to the field of maintenance and management technology, and in particular to a method and system for monitoring and early warning of landscaping maintenance. Background Technology

[0002] As the scale of urban green spaces continues to expand, the management of garden plants is gradually shifting from single-area management to multi-area and multi-type plant collaborative management. In the actual maintenance process, it is necessary to identify potential risks based on plant growth status, environmental changes, and historical maintenance processes, and to formulate corresponding maintenance measures in a timely manner to ensure the stable operation of green spaces.

[0003] Existing landscaping maintenance monitoring and early warning systems typically collect environmental status information, plant status change information, and historical maintenance records of the landscaping area to analyze whether there are current issues such as water shortage, abnormal growth, or disease risks in the area, and generate corresponding maintenance early warning information based on the analysis results.

[0004] In existing technologies, the monitoring and early warning process for landscaping maintenance typically generates early warning results based on the current risk status or preset maintenance rules. Although it can trigger corresponding maintenance measures based on abnormal states, in actual operation, there is a lack of effective correlation between the risk change process after the maintenance behavior is executed and the initial early warning result. This makes it impossible to adjust the subsequent early warning judgment process according to the actual maintenance response. At the same time, there may be mutual influence between multiple consecutive maintenance behaviors, but existing methods usually analyze single maintenance behaviors independently, which is difficult to adapt to the risk change patterns in the continuous maintenance process. In addition, existing methods lack targeted analysis and adjustment mechanisms for the deviation between the actual risk change results and the predicted results, making it difficult for the risk early warning process to continuously adapt to the actual operation in different regions and different maintenance stages.

[0005] Therefore, existing technologies suffer from insufficient correlation between risk warning results and maintenance execution feedback during the monitoring and early warning process for landscaping maintenance, resulting in poor adaptability of early warning adjustments. Summary of the Invention

[0006] This application provides a monitoring and early warning method and system for landscaping maintenance, which solves the problem in the prior art that the correlation between risk warning results and maintenance execution feedback is insufficient, resulting in poor adaptability of early warning adjustments. It realizes dynamic correction of risk warning results based on the maintenance behavior response process, improves the matching degree between risk judgment and actual maintenance status in the landscaping maintenance process, and enhances the continuous adaptability of the monitoring and early warning process.

[0007] This application provides a method for monitoring and early warning of landscaping maintenance, including: acquiring information on changes in the risk status of a target area, historical maintenance behavior execution information, and risk handling results information, and establishing a record linking risk events with maintenance behaviors;

[0008] Based on the risk status change information, risk event stages are divided, and a risk evolution record is established;

[0009] Based on the risk evolution record and the correlation record between the risk event and the maintenance behavior, an initial risk warning result and the expected risk change process are generated;

[0010] Obtain the actual maintenance behavior process performed in response to the current risk event, compare the actual risk status change process with the expected risk change process, and determine the change deviation;

[0011] Based on the execution time, risk status change process, and risk treatment results of multiple consecutive maintenance behaviors in history, the mechanism of maintenance behavior is analyzed, and a record of the impact relationship of maintenance behavior is established.

[0012] Based on the records of the impact of maintenance behaviors, the initial risk warning results are revised to form an updated risk warning record; and based on the recorded changes and deviations, the risk judgment threshold conditions, the matching logic relationship between maintenance behaviors and risk types, and the judgment rules for the risk recovery stage are adjusted.

[0013] Furthermore, establish a record linking risk events and maintenance behaviors, specifically including:

[0014] The information on changes in risk status includes the process of abnormal plant status changes, the process of environmental status changes, and the process of continuous risk changes.

[0015] The historical maintenance execution information includes the type of maintenance action, the time of execution of the maintenance action, the order of execution of the maintenance action, and the area affected by the maintenance action;

[0016] The risk handling result information includes the risk recovery time, the direction of risk status change, and the risk recovery process.

[0017] Analyze the risk status change information to determine the risk event records corresponding to the target area;

[0018] Match the risk event records with the historical maintenance behavior execution information executed within the corresponding time range;

[0019] The successfully matched risk event records, historical maintenance behavior execution information, and risk handling result information are combined to construct the risk event and maintenance behavior association record.

[0020] Furthermore, establish a risk evolution record, specifically including:

[0021] Based on the risk status change information, the risk event is divided into four evolutionary stages, including:

[0022] Identify the risk formation stage to record the evolution of the target area from a normal state to an abnormal state;

[0023] Determine the risk development stage to record the continuous changes in the abnormal state;

[0024] The risk diffusion stage is used to record the process by which the scope of the abnormal state expands or a consistent risk state appears in the corresponding area;

[0025] The risk recovery phase is defined to record the process by which the risk status gradually decreases and recovers to a preset normal range after maintenance is performed.

[0026] The risk evolution record is generated by summarizing the changes in risk status corresponding to the four evolution stages.

[0027] Furthermore, the initial risk warning results and the expected risk change process are generated, specifically including:

[0028] Extract the risk type and regional characteristics from the risk evolution record of the current risk event;

[0029] Search the historical records of similar risk events in the association records between the risk events and maintenance activities;

[0030] Analyze the changes, maintenance processes, and recovery results of similar historical risk events to determine the current risk development trend;

[0031] The initial risk warning result is generated based on the risk development trend;

[0032] Match the maintenance behavior execution records corresponding to the initial risk warning results;

[0033] The expected risk change process, including the expected risk reduction time, the direction of change, and the recovery phase, is determined based on the maintenance behavior execution records.

[0034] Furthermore, the actual risk status change process is compared with the expected risk change process to determine the deviation, specifically including:

[0035] Collect data on the types of maintenance activities, execution time, execution sequence, and affected areas of the maintenance activities during the actual implementation of maintenance procedures.

[0036] Continuously acquire information on the changes in the actual risk status after the execution of maintenance actions;

[0037] When the comprehensive change deviation index is greater than the preset deviation threshold, and the actual risk status change direction is consistent with the expected risk change direction, and the actual recovery time is greater than the expected risk reduction time, the corresponding risk event will be marked as a response cycle deviation event.

[0038] When the actual risk status does not change in the expected direction of risk change, the corresponding risk event will be marked as a risk development deviation event.

[0039] When the direction of change of the actual risk status is consistent with the direction of change of the expected risk, but the decrease of the actual risk indicator is less than the decrease of the expected risk indicator, the corresponding risk event will be marked as a recovery deviation event.

[0040] The different types of variation deviations are attributed and recorded to the corresponding maintenance behaviors.

[0041] Further steps in analyzing the mechanisms of maintenance behavior and establishing a record of the impact relationships of maintenance behavior include:

[0042] Acquire records of multiple maintenance actions performed within a continuous historical timeframe and analyze their interactions;

[0043] When multiple maintenance actions are performed consecutively, and the recovery of the risk status is accelerated and consistent with the expected process, a collaborative relationship record is established;

[0044] When multiple maintenance actions are performed consecutively, and the risk status recovery slows down, repeats itself, or is delayed, an interference relationship record is constructed.

[0045] When multiple maintenance actions are performed consecutively, and there is no clear logical linkage between changes in risk status, an independent relationship record is established;

[0046] By summarizing the collaborative relationship records, the interference relationship records, and the independent relationship records, the maintenance behavior influence relationship records are generated.

[0047] Furthermore, the steps to revise the initial risk warning results include:

[0048] When a new risk event occurs, extract its risk type, regional characteristics, and risk stage;

[0049] Query the records of the impact relationships of the maintenance activities to determine whether there are historical interference or synergistic relationships in the planned combination of maintenance activities;

[0050] When the historical interference relationship exists, the estimated risk recovery time is increased based on the ratio of the actual recovery time to the expected recovery time recorded in the historical interference relationship record, and the predicted duration of the recovery phase in the risk persistence phase is extended, the frequency of maintenance tracking and observation is increased, and the expected risk reduction time, expected risk change direction and expected recovery phase trajectory in the expected risk change process are updated, and the initial risk warning result is adjusted.

[0051] When the historical collaboration relationship exists, the estimated risk recovery time is lowered based on the ratio of the actual recovery time to the expected recovery time recorded in the historical collaboration relationship record, the estimated maintenance response time is shortened, and the expected risk reduction time, change direction and expected recovery stage trajectory in the expected risk change process are updated, and the initial risk warning result is adjusted.

[0052] The revised risk change trend, the impact of maintenance behavior, and the risk recovery process are combined and saved.

[0053] Furthermore, updated risk warning records are generated for subsequent monitoring and early warning, specifically including:

[0054] The data, including the revised risk change trend, the impact of maintenance behavior, and the risk recovery process, are archived to generate the updated risk warning record;

[0055] During subsequent maintenance and monitoring, data on newly added risk events will be received;

[0056] The updated risk warning records are used to analyze the evolution trend of the newly added risk events;

[0057] Based on the comparison deviation between the prediction results recorded in the updated risk warning record and the actual execution results, the risk judgment threshold conditions in the current risk warning process are adjusted.

[0058] Optimize the logical relationship between maintenance behaviors and risk types;

[0059] Update the judgment rules for the risk recovery phase to enable adaptive adjustments in subsequent monitoring and early warning processes.

[0060] This application provides a landscape greening maintenance monitoring and early warning system, which implements a landscape greening maintenance monitoring and early warning method, including: an association record establishment module, a risk evolution record establishment module, an initial result generation module, a change deviation determination module, an influence relationship record establishment module, and a risk early warning record update module;

[0061] The associated record establishment module is used to obtain risk status change information, historical maintenance behavior execution information, and risk handling result information of the target area, and establish an associated record of risk events and maintenance behaviors.

[0062] The risk evolution record establishment module is used to divide risk event stages according to the risk status change information and establish a risk evolution record.

[0063] The initial result generation module is used to generate an initial risk warning result and an expected risk change process based on the risk evolution record and the risk event and maintenance behavior association record.

[0064] The change deviation determination module is used to acquire the maintenance behavior process actually performed in response to the current risk event, compare the actual risk status change process with the expected risk change process, and determine the change deviation.

[0065] The influence relationship record establishment module is used to analyze the mechanism of maintenance behavior and establish an influence relationship record of maintenance behavior based on the execution time, risk status change process and risk treatment results of multiple consecutive maintenance behaviors in history.

[0066] The risk warning record update module is used to combine the maintenance behavior impact relationship record to correct the initial risk warning result and form an updated risk warning record; and to adjust the risk judgment threshold condition, the matching logic relationship between maintenance behavior and risk type, and the judgment rules of risk recovery stage according to the recorded change deviation.

[0067] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0068] By acquiring information on changes in risk status, historical maintenance practices, and risk management outcomes, a correlation between risk events and maintenance practices is established. Furthermore, risk evolution stages are divided based on the process of risk status changes, enabling the risk warning process to be analyzed in conjunction with the occurrence, development, and recovery of risks. This avoids making judgments solely based on the current abnormal state and improves the adaptability of risk identification and warning results in the process of landscaping maintenance.

[0069] Furthermore, when generating initial risk warning results, the expected risk change process is determined by combining the maintenance execution process and recovery results corresponding to similar historical risk events. The actual risk status change process after execution is compared with the expected change process to identify different types of change deviations. This allows the risk warning results to be adjusted according to the actual maintenance response, improving the correlation between the risk warning process and the actual maintenance process, and avoiding mismatch between the warning results and the actual risk development due to differences in maintenance behavior responses.

[0070] Furthermore, in the process of revising the risk warning results, the synergistic, interference, and independent relationships among multiple continuous maintenance behaviors are analyzed, and the subsequent warning judgment process is adjusted in combination with the impact of historical maintenance behaviors on the risk recovery process. This allows the risk change patterns under different combinations of maintenance behaviors to be continuously utilized, improving the continuous adaptability of the monitoring and early warning process for landscaping maintenance and reducing risk judgment bias caused by the repeated use of unsuitable maintenance strategies. Attached Figure Description

[0071] Figure 1 This application provides a flowchart of a method for monitoring and early warning of landscaping maintenance.

[0072] Figure 2 This is a structural schematic diagram of a landscape greening maintenance monitoring and early warning system provided in this application. Detailed Implementation

[0073] This application provides a method and system for monitoring and early warning of landscaping maintenance, which solves the problem in the prior art where the correlation between risk warning results and the execution process of maintenance behavior is insufficient, resulting in risk judgment being unable to adapt to actual maintenance changes. By establishing a record of the correlation between risk events and maintenance behavior, an initial warning result is generated based on the risk evolution process, and the warning result is dynamically corrected by combining the deviation of risk changes after actual maintenance and the influence relationship of maintenance behavior. This improves the matching degree between risk warning results and actual maintenance status, and realizes dynamic monitoring and adaptive early warning adjustment in the process of landscaping maintenance.

[0074] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0075] like Figure 1 The diagram shown is a flowchart of a landscape greening maintenance monitoring and early warning method provided in an embodiment of this application. The method is applied to a landscape greening maintenance monitoring and early warning system. The method includes the following steps: obtaining risk status change information, historical maintenance behavior execution information and risk handling result information of the target area, and establishing a record of the association between risk events and maintenance behaviors;

[0076] Based on the risk status change information, risk event stages are divided, and a risk evolution record is established;

[0077] Based on the risk evolution record and the correlation record between the risk event and the maintenance behavior, an initial risk warning result and the expected risk change process are generated;

[0078] Obtain the actual maintenance behavior process performed in response to the current risk event, compare the actual risk status change process with the expected risk change process, and determine the change deviation;

[0079] Based on the execution time, risk status change process, and risk treatment results of multiple consecutive maintenance behaviors in history, the mechanism of maintenance behavior is analyzed, and a record of the impact relationship of maintenance behavior is established.

[0080] Based on the records of the impact of maintenance behaviors, the initial risk warning results are revised to form an updated risk warning record; and based on the recorded changes and deviations, the risk judgment threshold conditions, the matching logic relationship between maintenance behaviors and risk types, and the judgment rules for the risk recovery stage are adjusted.

[0081] Furthermore, establish a record linking risk events and maintenance behaviors, specifically including:

[0082] The information on changes in risk status includes the process of abnormal plant status changes, the process of environmental status changes, and the process of continuous risk changes.

[0083] The historical maintenance execution information includes the type of maintenance action, the time of execution of the maintenance action, the order of execution of the maintenance action, and the area affected by the maintenance action;

[0084] The risk handling result information includes the risk recovery time, the direction of risk status change, and the risk recovery process.

[0085] Analyze the risk status change information to determine the risk event records corresponding to the target area;

[0086] Match the risk event records with the historical maintenance behavior execution information executed within the corresponding time range;

[0087] The successfully matched risk event records, historical maintenance behavior execution information, and risk handling result information are combined to construct the risk event and maintenance behavior association record.

[0088] In this embodiment, three types of data for the target garden maintenance area are first obtained from the system database or front-end business interface: risk status change information, historical maintenance behavior execution information, and risk handling result information.

[0089] Data analysis and content composition:

[0090] Information on changes in risk status: Specifically, this includes the process of changes in abnormal plant status, such as changes in the rate of yellowing leaves, changes in the degree of leaf wilting, the rate of lesion spread, the process of changes in environmental status, such as changes in soil moisture content, changes in near-surface air humidity, changes in extreme environmental temperatures, and the process of continuous changes in risk (the time span and stage accumulation from the occurrence of the risk to the present).

[0091] Historical maintenance behavior execution information: This includes the type of maintenance behavior, such as pesticide spraying, precision irrigation, pruning dead branches, soil fertilization, the time of execution of maintenance behavior (time stamp down to the minute), the order of execution of maintenance behavior (sequential order of multiple behaviors), and the area affected by maintenance behavior (geofence or tree number range).

[0092] Risk management outcome information includes: risk recovery time, i.e. the time difference between the implementation of maintenance and the return of indicators to the preset normal value; the direction of risk status change, such as the decline, stabilization or rebound of risk indicators; and the risk recovery process, such as linear recovery or stepwise recovery.

[0093] Data association and combinational logic:

[0094] Extract the abnormal start time point from the risk status change information and match the historical maintenance behavior execution information that occurred in the target area within a preset observation window after that time point (such as within 48 hours before and after).

[0095] By analyzing information on changes in risk status, risk event records are identified. Successfully matched maintenance actions with overlapping areas are then linked to risk management results, constructing and storing a "risk event and maintenance action association record." This step transforms raw, fragmented data into logically related data, resolving the issue of data separation between early warning and actual maintenance actions in existing technologies.

[0096] Furthermore, establish a risk evolution record, specifically including:

[0097] Based on the risk status change information, the risk event is divided into four evolutionary stages, including:

[0098] Identify the risk formation stage to record the evolution of the target area from a normal state to an abnormal state;

[0099] Determine the risk development stage to record the continuous changes in the abnormal state;

[0100] The risk diffusion stage is used to record the process by which the scope of the abnormal state expands or a consistent risk state appears in the corresponding area;

[0101] The risk recovery phase is defined to record the process by which the risk status gradually decreases and recovers to a preset normal range after maintenance is performed.

[0102] The risk evolution record is generated by summarizing the changes in risk status corresponding to the four evolution stages.

[0103] In this embodiment, based on the received information on changes in risk status, the current risk event's development status is divided into stages to depict the entire lifecycle of risk evolution. The division criteria are as follows:

[0104] Risk formation stage: Records the process of the target area transitioning from a normal state to an abnormal state. The formation stage begins when the monitored abnormal plant indicators or environmental indicators first exceed the preset safety threshold.

[0105] Risk Development Stage: Records the process of the abnormal state continuously deteriorating or accumulating. In this stage, abnormal plant indicators continue to rise, or the duration of the adverse environmental state reaches a preset duration threshold.

[0106] Risk diffusion stage: Record the process of the abnormal status affecting an expanding area. Determine whether similar abnormal indicators appear in adjacent geographical areas (such as green belts within a 50-meter radius), or whether the proportion of abnormal plants in the same area increases.

[0107] Risk recovery phase: This records the process by which the risk level gradually decreases and approaches normal levels after maintenance measures are implemented. The recovery phase is defined as when abnormal indicators show a sustained decline without rebounding.

[0108] The computing device summarizes the time nodes, indicator values, and evolution trajectories of the above four stages to generate a "risk evolution record" corresponding to the risk event.

[0109] Furthermore, the initial risk warning results and the expected risk change process are generated, specifically including:

[0110] Extract the risk type and regional characteristics from the risk evolution record of the current risk event;

[0111] Search the historical records of similar risk events in the association records between the risk events and maintenance activities;

[0112] Analyze the changes, maintenance processes, and recovery results of similar historical risk events to determine the current risk development trend;

[0113] The initial risk warning result is generated based on the risk development trend;

[0114] Match the maintenance behavior execution records corresponding to the initial risk warning results;

[0115] The expected risk change process, including the expected risk reduction time, the direction of change, and the recovery phase, is determined based on the maintenance behavior execution records.

[0116] In this embodiment, the evolution record of the current risk event is extracted to obtain the risk type and regional characteristics, and historical similar risk events of the same type and regional characteristics are retrieved from the database. By jointly analyzing the evolution process and recovery results of historical similar risk events, the development trend of the current risk event is calculated, and an initial risk warning result is generated.

[0117] Risk trend score is calculated using a risk development trend scoring algorithm. :

[0118] ;

[0119] In the formula, The score represents the current risk development trend, with a dimensionless value ranging from zero to one. A higher value indicates a stronger trend of risk deterioration. The measured values ​​of current abnormal plant indicators, such as the proportion of damaged leaves, are obtained through sensor or manual inspection data input, and the values ​​are non-negative. This is the preset maximum extreme abnormal threshold corresponding to this risk type, such as a 100% complete leaf necrosis rate, which is a preset constant. ,in ,For example and All values ​​are 0.5; The normalized value for environmental temperature stress was obtained using min-max normalization. , To measure the ambient temperature, , These are the lower and upper limits of the suitable growth temperature for this plant variety, respectively. Values ​​exceeding the range of 0 to 1 are taken as boundary values. This represents the normalized value of soil drought. , This represents the lower limit of suitable soil moisture content for this plant variety. The measured soil moisture content ranges from 0 to 1. The duration of the current risk, in hours, is obtained by subtracting the start time of the risk formation phase from the current timestamp. This is a standard risk assessment cycle constant, for example, a value of 72 hours; Indicates taking and The smaller value in the range, i.e., when the duration of the risk exceeds the standard risk assessment period, is used to determine the risk development trend score. The value of is no more than 1. These are weighting coefficients, all greater than 0 and satisfying... When implementing this in small and medium-sized companies, the initial setup can be set to... .

[0120] Calculated Match the preset warning levels (e.g., low, medium, high risk) to generate initial risk warning results, and retrieve historical maintenance behavior execution records that match the warning level to extract information including the expected risk reduction time. The "expected risk change process" refers to the expected direction of change and the trajectory of the expected recovery phase.

[0121] Furthermore, the actual risk status change process is compared with the expected risk change process to determine the deviation, specifically including:

[0122] Collect data on the types of maintenance activities, execution time, execution sequence, and affected areas of the maintenance activities during the actual implementation of maintenance procedures.

[0123] Continuously acquire information on the changes in the actual risk status after the execution of maintenance actions;

[0124] When the comprehensive change deviation index is greater than the preset deviation threshold, and the actual risk status change direction is consistent with the expected risk change direction, and the actual recovery time is greater than the expected risk reduction time, the corresponding risk event will be marked as a response cycle deviation event.

[0125] When the actual risk status does not change in the expected direction of risk change, the corresponding risk event will be marked as a risk development deviation event.

[0126] When the direction of change of the actual risk status is consistent with the direction of change of the expected risk, but the decrease of the actual risk indicator is less than the decrease of the expected risk indicator, the corresponding risk event will be marked as a recovery deviation event.

[0127] Based on the overlap between the area of ​​effect and the area where the risk event is located, the order of priority of the maintenance behavior execution time being closest to the deviation determination time point, and the order of execution being the last, the different types of change deviations and the corresponding maintenance behaviors are attributed and recorded.

[0128] In this embodiment, after the initial risk warning result is pushed out, on-site personnel or automated equipment will perform actual maintenance actions in response to the current risk event. The system continuously collects data on the type of action, execution time, execution sequence, and affected area during the actual maintenance process, and monitors changes in the risk status after execution in real time.

[0129] The actual risk status change process is compared with the previously generated expected risk change process to calculate the comprehensive change deviation index. :

[0130] ;

[0131] In the formula, The comprehensive deviation index has a value that is not less than zero. The larger the value, the more serious the deviation between the actual recovery effect and the expectation. The actual time required to restore to normal status is calculated by subtracting the maintenance execution timestamp from the restoration completion timestamp. The time required for the anticipated risk reduction or recovery is extracted from the process of anticipated risk changes. The reduction in actual risk indicators, such as a decrease in the yellowing rate by percentage points, is calculated based on actual measurements after maintenance. The expected reduction in risk indicators is extracted from the process of expected risk changes. , These are proportional balance factors, all of which are positive and satisfy the following conditions: For example, they can be set to 0.4 and 0.6 respectively. This is a standard risk assessment cycle constant, used in the aforementioned risk development trend score calculation. It is the same constant, for example, with a value of 72 hours, used to normalize the time deviation term.

[0132] Bias detection and attribution labeling logic:

[0133] when When the deviation exceeds a preset threshold, the current risk event is determined to have a change deviation, and the deviation type is identified according to the following rules; when If the deviation is not greater than the preset deviation threshold, the actual risk status change is determined to be basically consistent with the expected risk change, and deviation attribution and early warning correction are not initiated. The preset deviation threshold is set by the management personnel according to the maintenance accuracy requirements.

[0134] Response cycle deviation event:

[0135] When the actual risk state changes in the same direction as the expected risk change, i.e., the risk decreases, but the actual recovery time is longer than the expected risk reduction time (i.e., (Marked when...)

[0136] Risk development deviation event: When the actual risk status does not change in the direction of expected risk change, such as when the risk index increases instead of decreasing after maintenance.

[0137] Recovery deviation event: When the direction of change is the same, but the actual decrease in risk indicators is less than the expected decrease in risk indicators (i.e., (Marked when...)

[0138] Based on the overlap between the area of ​​effect and the area of ​​the risk event, the order of priority (closest to the deviation determination point in terms of the execution time of the maintenance behavior), and the order of execution (last in priority), the above-mentioned different types of change deviations are attributed and associated with the corresponding maintenance behaviors. The deviation type and its corresponding comprehensive change deviation index are then listed. The deviation between the actual recovery time and the expected recovery time, along with the type of maintenance behavior attributable to it, are recorded in the attribution record and stored to provide a basis for later optimization. The recorded deviations are used to adjust subsequent risk assessment threshold conditions, the matching logic between maintenance behaviors and risk types, and the rules for judging the risk recovery stage.

[0139] Further steps in analyzing the mechanisms of maintenance behavior and establishing a record of the impact relationships of maintenance behavior include:

[0140] Acquire records of multiple maintenance actions performed within a continuous historical timeframe and analyze their interactions;

[0141] Among them, "continuous" means that the time interval between the execution of two adjacent maintenance actions does not exceed the preset continuous judgment window. This continuous judgment window is consistent with the observation window used when matching the historical maintenance action execution information, for example, 48 hours.

[0142] When multiple maintenance actions are performed consecutively, and the recovery of the risk status is accelerated and consistent with the expected process, a collaborative relationship record is established;

[0143] When multiple maintenance actions are performed consecutively, and the risk status recovery slows down, repeats itself, or is delayed, an interference relationship record is constructed.

[0144] When multiple maintenance actions are performed consecutively, and there is no clear logical linkage between changes in risk status, an independent relationship record is established;

[0145] By summarizing the collaborative relationship records, the interference relationship records, and the independent relationship records, the maintenance behavior influence relationship records are generated.

[0146] In this embodiment, in actual garden maintenance, multiple maintenance behaviors are often performed consecutively within a short period of time, such as pruning before fertilizing, or irrigating and spraying pesticides simultaneously. By analyzing the execution time relationship, risk status changes, and recovery results of multiple consecutive maintenance behaviors in history, the interaction between different behaviors is determined.

[0147] When determining the mechanism of action of a combination of multiple maintenance behaviors, the sum of the historical average recovery rates when each maintenance behavior is performed individually is used as the comparison benchmark: Define the combined recovery benchmark rate:

[0148] ;

[0149] In the formula, This is the baseline for the natural recovery rate of risk when no maintenance is performed, and is usually taken as 0 or a constant derived from historical no-maintenance data. For the first The historical average recovery rate when a maintenance action is performed individually is extracted from the historical records associated with individual actions. The total number of maintenance actions performed consecutively is a positive integer greater than or equal to 2. For continuous execution The actual observed recovery rate of risk status after a maintenance action, i.e., the decrease in abnormal indicators per unit time.

[0150] Will and Compare and determine the mechanisms of action among multiple maintenance behaviors according to the following rules:

[0151] when When the combined effect is significantly greater than the sum of the individual effects of each maintenance behavior, it indicates that the risk status is recovering faster and the recovery process is consistent with expectations. Therefore, records of synergistic relationships should be constructed and saved.

[0152] when When the combined effect is significantly lower than the sum of the individual effects of each maintenance behavior, it indicates that the risk status recovery is slower, there are repeated changes, or the recovery is delayed. Therefore, interference relationship records should be constructed and saved.

[0153] when When the combined effect is roughly equivalent to the sum of the individual effects of each maintenance action, it indicates that there is no clear logical linkage between multiple maintenance actions, and independent relationship records are constructed and saved.

[0154] The aforementioned 15% is a tolerance percentage for determining whether the combined effect significantly deviates from the sum of the individual effects of each behavior, and can be set by those skilled in the art according to the maintenance accuracy requirements. The constructed records of synergistic relationships, interference relationships, and independent relationships all store the actual recovery time, expected recovery time, actual recovery speed, and expected recovery speed corresponding to the maintenance behavior combination, for use when subsequently revising the initial risk warning results.

[0155] Furthermore, the steps to revise the initial risk warning results include:

[0156] When a new risk event occurs, extract its risk type, regional characteristics, and risk stage;

[0157] Query the records of the impact relationships of the maintenance activities to determine whether there are historical interference or synergistic relationships in the planned combination of maintenance activities;

[0158] When the aforementioned historical interference relationship exists, the estimated risk recovery time is adjusted upward based on the ratio of the actual recovery time to the expected recovery time recorded in the historical interference relationship record; that is, the adjusted estimated risk recovery time. Original estimated risk recovery time (Historical actual recovery time) Historical expected recovery time), and extend the predicted duration of the recovery phase in the risk persistence phase, increase the frequency of maintenance tracking and observation, for example, increase the observation frequency from once a day to three times a day, and update the expected risk reduction time, change direction and expected recovery phase trajectory in the expected risk change process, and adjust the initial risk warning result;

[0159] When the historical collaboration relationship exists, the estimated risk recovery time is lowered based on the ratio of the actual recovery time to the expected recovery time recorded in the historical collaboration relationship record, the estimated maintenance response time is shortened, and the expected risk reduction time, change direction and expected recovery stage trajectory in the expected risk change process are updated, and the initial risk warning result is adjusted.

[0160] The revised risk change trend, the impact of maintenance behavior, and the risk recovery process are combined and saved.

[0161] In this embodiment, when a new risk event occurs and a maintenance plan is to be formulated, the type, region and development stage of the current risk event are extracted, the "maintenance behavior impact relationship record" in the database is queried, and the historical relationship of the current planned maintenance behavior combination is verified.

[0162] Adjustments in the presence of interference: When a planned action combination is determined to have a historical interference relationship, an early warning adjustment logic is triggered. The estimated risk recovery time is increased based on the ratio of the actual recovery time to the expected recovery time recorded in the historical interference relationship record. Original estimated risk recovery time (Historical actual recovery time) Historical expected recovery time); extend the predicted duration of the recovery phase in the risk persistence phase by the same ratio; and automatically extend the subsequent maintenance tracking and observation cycle, for example, increase the observation frequency from once a day to three times a day; at the same time, update the expected risk reduction time, change direction and expected recovery phase trajectory in the expected risk change process.

[0163] Adjustments when a synergy exists: When a combination of planned actions is determined to have a historical synergy, the estimated risk recovery time is reduced by the ratio of the actual recovery time to the expected recovery time recorded in the historical synergy record. This results in the reduced estimated risk recovery time. Original estimated risk recovery time (Historical actual recovery time) Historical expected recovery time), and correspondingly shorten the estimated maintenance response time; at the same time, update the expected risk reduction time, change direction and expected recovery phase trajectory in the process of expected risk changes.

[0164] The adjusted risk change trends, impact relationships, and recovery processes are combined and stored to form a revised early warning plan for the current risk.

[0165] Furthermore, updated risk warning records are generated for subsequent monitoring and early warning, specifically including:

[0166] The data, including the revised risk change trend, the impact of maintenance behavior, and the risk recovery process, are archived to generate the updated risk warning record;

[0167] During subsequent maintenance and monitoring, data on newly added risk events will be received;

[0168] The updated risk warning records are used to analyze the evolution trend of the newly added risk events;

[0169] Based on the comparison deviation between the prediction results recorded in the updated risk warning record and the actual execution results, the risk judgment threshold conditions in the current risk warning process are adjusted.

[0170] Optimize the logical relationship between maintenance behaviors and risk types;

[0171] Update the judgment rules for the risk recovery phase to enable adaptive adjustments in subsequent monitoring and early warning processes.

[0172] In this embodiment, the revised risk change trend, the impact of maintenance behavior, and the risk recovery process are archived and saved, and the risk warning record library in the database is updated.

[0173] In subsequent new greening monitoring processes:

[0174] Receive data on newly occurring risk events and retrieve updated risk warning records for trend analysis.

[0175] Based on the deviations between historical predictions and actual results, the threshold conditions for current risk assessment are dynamically adjusted, with the adjustment direction consistent with the direction of the deviation: when the deviation manifests as an actual recovery time later than expected or an actual recovery magnitude less than expected, the critical score for high risk is lowered, thus raising the warning level for the same risk development trend score; when the deviation manifests as an actual recovery time earlier than expected or an actual recovery magnitude greater than expected, the critical score is raised; the adjustment magnitude is correlated with the comprehensive change deviation index corresponding to the deviation. Positive correlation.

[0176] Optimize the matching rules for maintenance behaviors, discard combinations that were historically marked as interfering, and prioritize combinations of behaviors marked as synergistic, thereby achieving adaptive evolution of the monitoring and early warning process.

[0177] like Figure 2The diagram shown is a structural schematic of a landscape greening maintenance monitoring and early warning system provided in an embodiment of this application. The landscape greening maintenance monitoring and early warning system provided in this embodiment of this application includes: an association record establishment module, a risk evolution record establishment module, an initial result generation module, a change deviation determination module, an influence relationship record establishment module, and a risk early warning record update module.

[0178] The associated record establishment module is used to obtain risk status change information, historical maintenance behavior execution information, and risk handling result information of the target area, and establish an associated record of risk events and maintenance behaviors.

[0179] The risk evolution record establishment module is used to divide risk event stages according to the risk status change information and establish a risk evolution record;

[0180] The initial result generation module is used to generate an initial risk warning result and the expected risk change process based on the risk evolution record and the risk event and maintenance behavior association record.

[0181] The change deviation determination module is used to acquire the maintenance behavior process actually performed in response to the current risk event, compare the actual risk status change process with the expected risk change process, and determine the change deviation.

[0182] The influence relationship record establishment module is used to analyze the mechanism of maintenance behavior and establish an influence relationship record of maintenance behavior based on the execution time, risk status change process and risk treatment results of multiple consecutive maintenance behaviors in history.

[0183] The risk warning record update module is used to combine the maintenance behavior impact relationship record to correct the initial risk warning result and form an updated risk warning record; and to adjust the risk judgment threshold condition, the matching logic relationship between maintenance behavior and risk type, and the judgment rules of risk recovery stage according to the recorded change deviation.

[0184] The proportional coefficients, weighting coefficients, and constants in the above formulas are all set based on historical monitoring data of the target maintenance area, and are adjusted and updated by those skilled in the art based on the plant type, maintenance precision requirements, and actual risk changes in the area.

[0185] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0186] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0187] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0188] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0189] Finally: The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for monitoring and early warning of landscaping maintenance, characterized in that, Includes the following steps: Acquire information on changes in the risk status of the target area, historical maintenance execution information, and risk handling results, and establish a record linking risk events with maintenance actions; Based on the risk status change information, risk event stages are divided, and a risk evolution record is established; Based on the risk evolution record and the correlation record between the risk event and the maintenance behavior, an initial risk warning result and the expected risk change process are generated; Obtain the actual maintenance behavior process performed in response to the current risk event, compare the actual risk status change process with the expected risk change process, and determine the change deviation; Based on the execution time, risk status change process, and risk treatment results of multiple consecutive maintenance behaviors in history, the mechanism of maintenance behavior is analyzed, and a record of the impact relationship of maintenance behavior is established. Based on the records of the impact of the maintenance activities, the initial risk warning results are revised to form an updated risk warning record.

2. The method for monitoring and early warning of landscaping maintenance as described in claim 1, characterized in that, Establish a record linking risk events and maintenance activities, specifically including: The information on changes in risk status includes the process of abnormal plant status changes, the process of environmental status changes, and the process of continuous risk changes. The historical maintenance execution information includes the type of maintenance action, the time of execution of the maintenance action, the order of execution of the maintenance action, and the area affected by the maintenance action; The risk handling result information includes the risk recovery time, the direction of risk status change, and the risk recovery process. Analyze the risk status change information to determine the risk event records corresponding to the target area; Match the risk event records with the historical maintenance behavior execution information executed within the corresponding time range; The successfully matched risk event records, historical maintenance behavior execution information, and risk handling result information are combined to construct the risk event and maintenance behavior association record.

3. The method for monitoring and early warning of landscaping maintenance as described in claim 1, characterized in that, Establish a risk evolution record, specifically including: Based on the risk status change information, the risk event is divided into four evolutionary stages, including: Identify the risk formation stage to record the evolution of the target area from a normal state to an abnormal state; Determine the risk development stage to record the continuous changes in the abnormal state; The risk diffusion stage is used to record the process by which the scope of the abnormal state expands or a consistent risk state appears in the corresponding area; The risk recovery phase is defined to record the process by which the risk status gradually decreases and recovers to a preset normal range after maintenance is performed. The risk evolution record is generated by summarizing the changes in risk status corresponding to the four evolution stages.

4. The method for monitoring and early warning of landscaping maintenance as described in claim 1, characterized in that, The process of generating initial risk warning results and anticipated risk changes includes: Extract the risk type and regional characteristics from the risk evolution record of the current risk event; Search the historical records of similar risk events in the association records between the risk events and maintenance activities; Analyze the changes, maintenance processes, and recovery results of similar historical risk events to determine the current risk development trend; The initial risk warning result is generated based on the risk development trend; Match the maintenance behavior execution records corresponding to the initial risk warning results; The expected risk change process, including the expected risk reduction time, the direction of change, and the recovery phase, is determined based on the maintenance behavior execution records.

5. The method for monitoring and early warning of landscaping maintenance as described in claim 1, characterized in that, The actual risk status change process is compared with the expected risk change process to determine the deviation, specifically including: Collect data on the types of maintenance activities, execution time, execution sequence, and affected areas of the maintenance activities during the actual implementation of maintenance procedures. Continuously acquire information on the changes in the actual risk status after the execution of maintenance actions; When the comprehensive change deviation index is greater than the preset deviation threshold, and the actual risk status change direction is consistent with the expected risk change direction, and the actual recovery time is greater than the expected risk reduction time, the corresponding risk event will be marked as a response cycle deviation event. When the actual risk status does not change in the expected direction of risk change, the corresponding risk event will be marked as a risk development deviation event. When the direction of change of the actual risk status is consistent with the direction of change of the expected risk, but the decrease of the actual risk indicator is less than the decrease of the expected risk indicator, the corresponding risk event will be marked as a recovery deviation event. The different types of variation deviations are attributed and recorded to the corresponding maintenance behaviors.

6. The method for monitoring and early warning of landscaping maintenance as described in claim 1, characterized in that, The steps to analyze the mechanism of maintenance behavior and establish a record of the impact relationships of maintenance behavior include: Acquire records of multiple maintenance actions performed within a continuous historical timeframe and analyze their interactions; When multiple maintenance actions are performed consecutively, and the recovery of the risk status is accelerated and consistent with the expected process, a collaborative relationship record is established; When multiple maintenance actions are performed consecutively, and the risk status recovery slows down, repeats itself, or is delayed, an interference relationship record is constructed. When multiple maintenance actions are performed consecutively, and there is no clear logical linkage between changes in risk status, an independent relationship record is established; By summarizing the collaborative relationship records, the interference relationship records, and the independent relationship records, the maintenance behavior influence relationship records are generated.

7. The method for monitoring and early warning of landscaping maintenance as described in claim 1, characterized in that, The steps to revise the initial risk warning results include: When a new risk event occurs, extract its risk type, regional characteristics, and risk stage; Query the records of the impact relationships of the maintenance activities to determine whether there are historical interference or synergistic relationships in the planned combination of maintenance activities; When the historical interference relationship exists, the estimated risk recovery time is increased based on the ratio of the actual recovery time to the expected recovery time recorded in the historical interference relationship record, and the predicted duration of the recovery phase in the risk persistence phase is extended, the frequency of maintenance tracking and observation is increased, and the expected risk reduction time, expected risk change direction and expected recovery phase trajectory in the expected risk change process are updated, and the initial risk warning result is adjusted. When the aforementioned historical collaborative relationship exists, shorten the estimated maintenance response time and adjust the initial risk warning result; The revised risk change trend, the impact of maintenance behavior, and the risk recovery process are combined and saved.

8. The method for monitoring and early warning of landscaping maintenance as described in claim 1, characterized in that, Updated risk warning records are generated for subsequent monitoring and early warning, specifically including: The data, including the revised risk change trend, the impact of maintenance behavior, and the risk recovery process, are archived to generate the updated risk warning record; During subsequent maintenance and monitoring, data on newly added risk events will be received; The updated risk warning records are used to analyze the evolution trend of the newly added risk events; Based on the comparison deviation between the prediction results recorded in the updated risk warning record and the actual execution results, the risk judgment threshold conditions in the current risk warning process are adjusted. Optimize the logical relationship between maintenance behaviors and risk types; Update the judgment rules for the risk recovery phase to enable adaptive adjustments in subsequent monitoring and early warning processes.

9. A landscape greening maintenance monitoring and early warning system, used to implement the landscape greening maintenance monitoring and early warning method according to any one of claims 1-8, characterized in that, include: The module includes modules for establishing correlation records, establishing risk evolution records, generating initial results, determining changes and deviations, establishing impact relationship records, and updating risk warning records. The associated record establishment module is used to obtain risk status change information, historical maintenance behavior execution information, and risk handling result information of the target area, and establish an associated record between risk events and maintenance behaviors. The risk evolution record establishment module is used to divide risk event stages according to the risk status change information and establish a risk evolution record. The initial result generation module is used to generate an initial risk warning result and an expected risk change process based on the risk evolution record and the risk event and maintenance behavior association record. The change deviation determination module is used to acquire the maintenance behavior process actually performed in response to the current risk event, compare the actual risk status change process with the expected risk change process, and determine the change deviation. The influence relationship record establishment module is used to analyze the mechanism of maintenance behavior and establish an influence relationship record of maintenance behavior based on the execution time, risk status change process and risk treatment results of multiple consecutive maintenance behaviors in history. The risk warning record update module is used to combine the maintenance behavior impact relationship record to correct the initial risk warning result and form an updated risk warning record.

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