An environment maintenance strategy generation method, device, equipment and storage medium

Abstract

The present disclosure provides an environment maintenance strategy generation method, device, equipment and storage medium. The method comprises: acquiring an environment layout map corresponding to a to-be-maintained environment; mapping historical pollution events occurring in the to-be-maintained environment to the environment layout map to obtain historical pollution areas in the to-be-maintained environment and pollution rules corresponding to the historical pollution areas, wherein the pollution rules comprise at least one of a pollution type rule, a pollution frequency rule, a pollution weather rule and a pollution time rule; and generating an environment maintenance strategy of the to-be-maintained environment according to the pollution rules. The present disclosure generates an environment maintenance strategy by summarizing pollution rules from long-term retained environment historical pollution data, without the need to inspect all areas in the subsequent environment maintenance process, thereby reducing invalid inspection distance and improving pollution cleaning efficiency.

Description

[0001] This disclosure claims priority to Singapore Patent Application No. 10202602822Y, filed on August 13, 2026, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This disclosure relates to the field of cleaning equipment technology, and in particular to a method, apparatus, device and storage medium for generating environmental maintenance strategies. Background Technology

[0003] With the rapid development of smart home technology, cleaning equipment has become a core component of smart home cleaning. These devices utilize technologies such as machine vision to achieve autonomous indoor navigation and automatic floor cleaning. If a contaminated area is detected within the device's field of vision, it will clean that area; otherwise, it will navigate along a preset route.

[0004] In existing technologies, cleaning equipment needs to re-examine the indoor environment to detect contaminated areas every time it is started. It lacks the ability to store and remember the indoor environment for a long time, and cannot carry out targeted cleaning of areas that are frequently contaminated, thus reducing the efficiency of pollution cleaning. Summary of the Invention

[0005] To address the aforementioned technical problems, this disclosure provides an environmental maintenance strategy generation method, apparatus, device, and storage medium to solve the problem that cleaning equipment cannot perform targeted cleaning of high-frequency polluted areas.

[0006] The first aspect of this disclosure provides a method for generating an environmental maintenance strategy, comprising: Obtain the environment layout map corresponding to the environment to be maintained; By mapping historical pollution events that occurred in the environment to be maintained onto the environmental layout map, the historical pollution areas in the environment to be maintained and the corresponding pollution patterns are obtained. Among them, the pollution patterns include at least one of the following: pollution type pattern, pollution frequency pattern, pollution weather pattern, and pollution time pattern. An environmental maintenance strategy is generated based on the pollution patterns. The environmental maintenance strategy includes at least one of a cleaning strategy and an inspection strategy.

[0007] A second aspect of this disclosure provides an environmental maintenance strategy generation apparatus, comprising: The acquisition module is used to acquire the environment layout map corresponding to the environment to be maintained. The event mapping module is used to map historical pollution events that occur in the environment to be maintained to the environmental layout map, so as to obtain the historical pollution areas in the environment to be maintained and the corresponding pollution patterns. The pollution patterns include at least one of the following: pollution type pattern, pollution frequency pattern, pollution weather pattern, and pollution time pattern. The strategy generation module is used to generate environmental maintenance strategies for the environment to be maintained based on pollution patterns. The environmental maintenance strategies include at least one of cleaning strategies and inspection strategies.

[0008] A third aspect of this disclosure provides a computer-readable storage medium storing a computer program for executing the environment maintenance strategy generation method provided in the first aspect of this disclosure.

[0009] A fourth aspect of this disclosure provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; A processor is configured to read executable instructions from memory and execute the instructions to implement the environment maintenance strategy generation method provided in the first aspect of this disclosure.

[0010] A fifth aspect of this disclosure provides a computer program product that, when executed by an instruction processor, performs the environment maintenance strategy generation method provided in the first aspect of this disclosure.

[0011] This disclosure provides an environmental maintenance strategy generation method, apparatus, device, and storage medium. First, an environmental layout map corresponding to the environment to be maintained is obtained. Then, historical pollution events occurring within the environment to be maintained are mapped onto the environmental layout map to obtain historical pollution areas and corresponding pollution patterns. These pollution patterns include at least one of pollution type patterns, pollution frequency patterns, pollution weather patterns, and pollution time patterns. Finally, an environmental maintenance strategy for the environment to be maintained is generated based on these pollution patterns. By mapping historical pollution events onto the environmental layout map and analyzing pollution patterns, cleaning equipment acquires long-term environmental learning and memory capabilities. This enables targeted cleaning of high-frequency pollution areas, dynamic inspection optimization, and the generation of preventative maintenance strategies. This addresses the problem of low cleaning efficiency and intelligence levels in existing cleaning equipment due to a lack of long-term environmental memory, thereby improving the cleaning efficiency and intelligence level of the cleaning equipment. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the architecture of a cleaning system provided in an embodiment of this disclosure; Figure 2 This is a flowchart illustrating an exemplary embodiment of the present disclosure of a method for generating an environmental maintenance strategy; Figure 3 This is a flowchart illustrating step S220 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure; Figure 4 This is a flowchart illustrating step S224 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure; Figure 5 This is a schematic diagram of the first step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of the present disclosure; Figure 6 This is a schematic diagram of the second step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure; Figure 7 This is a schematic diagram of the third step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure; Figure 8 This is a schematic diagram of the fourth step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure; Figure 9 This is a schematic diagram of the fifth step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure; Figure 10 This is a schematic diagram of the sixth step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure; Figure 11 This is a flowchart illustrating the process before step S220 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure; Figure 12 This is a schematic diagram of the structure of an environmental maintenance strategy generation device provided in an exemplary embodiment of the present disclosure; Figure 13 This is a structural diagram of an electronic device provided in an embodiment of the present disclosure. Detailed Implementation

[0013] To explain this disclosure, exemplary embodiments of the disclosure will now be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the disclosure, and not all of them. It should be understood that the disclosure is not limited to exemplary embodiments.

[0014] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of this disclosure.

[0015] Application Overview In the field of smart home technology, cleaning equipment (such as robotic vacuum cleaners and robot vacuums) can autonomously plan routes to clean indoor floors. However, current cleaning equipment can only perform cleaning according to fixed patterns, such as using fixed suction power, fixed cleaning routes, and fixed inspection frequencies. This makes it difficult to adapt to the different levels of pollution in different areas, resulting in low cleaning efficiency.

[0016] Specifically, existing cleaning equipment typically inspects and cleans the entire indoor area according to a designated inspection route each time it starts up, due to a lack of long-term environmental memory. However, indoor areas include those that remain clean for extended periods and those that frequently become contaminated. If the cleaning equipment inspects and cleans the areas that remain clean for extended periods every time it starts up, it undoubtedly wastes unnecessary inspection power. At the same time, it also affects the timeliness of inspecting and cleaning the areas that frequently become contaminated, thus reducing cleaning efficiency.

[0017] To address the aforementioned issues, this disclosure provides an environmental maintenance strategy generation method. This method maps historical pollution events onto an environmental layout map, analyzes at least one of the following: pollution type patterns, pollution frequency patterns, pollution weather patterns, and pollution time patterns, and dynamically generates an environmental maintenance strategy based on this at least one pollution pattern. This enables cleaning equipment to possess long-term environmental learning and memory capabilities, allowing for targeted cleaning of high-frequency pollution areas and dynamic optimization of inspection strategies. This solves the problem of existing cleaning equipment lacking long-term environmental memory, resulting in low cleaning efficiency and intelligence levels, thereby improving the cleaning efficiency and intelligence level of the cleaning equipment.

[0018] Exemplary System Figure 1 This is a schematic diagram of the architecture of a cleaning system provided in an embodiment of this disclosure. Figure 1 As shown in the embodiments of this disclosure, the environmental maintenance strategy generation method can be applied to a cleaning system, which includes a cleaning device 10 and a control device 20. The cleaning device 10 can perform cleaning tasks and collect environmental data in the environment to be maintained. The environment to be maintained is the area that the cleaning device 10 is responsible for inspecting and cleaning.

[0019] The control device 20 can interact with the cleaning device 10, for example, by receiving environmental data collected by the cleaning device 10, constructing an environmental layout map based on the environmental data collected by the cleaning device 10, recording historical pollution events, generating environmental maintenance strategies, and sending maintenance instructions to the cleaning device 10.

[0020] In one implementation, the cleaning device 10 can be a sweeping robot, a mopping robot, a sweeping and mopping robot in combination, a cleaning service robot, etc. The cleaning device 10 may include a sensor unit 11 and an actuator 12. The sensor unit 11 may include at least one of a vision sensor, a ranging sensor, an inertial sensor, and a status sensor.

[0021] Visual sensors, such as color (Red, Green, Blue, RGB) cameras, depth cameras, and panoramic cameras, are used to acquire environmental images of the environment to be maintained. Distance sensors, such as lidar, millimeter-wave radar, and time-of-flight (ToF) sensors, are used to measure the distance between the cleaning equipment 10 and objects in the environment to be maintained, and to construct a two-dimensional navigation map of the environment using simultaneous localization and mapping (SLAM) algorithms. Inertial sensors, such as inertial measurement units (IMUs) and odometry, are used for attitude estimation and trajectory calculation of the cleaning equipment 10. Status sensors, such as cliff sensors, collision sensors, and dustbin full sensors, are used for status monitoring and safety protection of the cleaning equipment 10. The actuator 12 includes a walking drive and a cleaning mechanism. The walking drive can be, for example, drive wheels or casters, and the cleaning mechanism can include at least one of a roller brush, side brush, suction motor, mop, and water pump.

[0022] In one implementation, the control device 20 can be deployed on a cloud server or a local device. The local device could be, for example, an Artificial Intelligence Personal Computer (AIPC), a smart speaker, or a home gateway. The control device 20 can deploy object detection models, such as the YOLO (You Only Look Once) model or the GroundingDINO visual language model, to detect information such as the type, location, and area of ​​pollutants from environmental images. The control device 20 can also deploy a large language model (LLM) for tasks such as semantic analysis of historical pollution data, feature extraction of pollution patterns, and generation of environmental maintenance strategies.

[0023] In one implementation, the cleaning device 10 may further include a communication unit 13 for supporting wired or wireless network communication methods such as Ethernet, Wi-Fi, and Bluetooth, to interact with the control device 20.

[0024] Exemplary methods Figure 2 This is a flowchart illustrating an exemplary embodiment of an environmental maintenance strategy generation method provided by this disclosure. This embodiment can be applied to cleaning equipment, or it can be executed collaboratively by a control device and a cleaning device. The following detailed description uses a cleaning device as the executing entity to illustrate the technical solution of this disclosure.

[0025] like Figure 2 As shown, the environmental maintenance strategy generation method provided in this embodiment includes the following steps: S210: Obtain the environment layout map corresponding to the environment to be maintained.

[0026] The environment to be maintained refers to the target area where cleaning equipment needs to perform environmental maintenance tasks. In one implementation, the environment to be maintained may include the ground areas of places such as homes, offices, shopping malls, restaurants, and hospitals. An environmental layout map refers to map data reflecting the spatial structure of the environment to be maintained.

[0027] In some examples, environmental layout maps can be constructed using sensor units mounted on the cleaning equipment. Specifically, during the initial startup and inspection of the environment to be maintained, the cleaning equipment can collect geometric and visual information of the environment to be maintained using sensors such as LiDAR and RGB cameras, and construct an environmental layout map of the environment to be maintained using the Simultaneous Localization and Mapping (SLAM) algorithm.

[0028] In one implementation, the environmental layout map can be a two-dimensional navigation map, which can include information such as room boundaries, wall locations, obstacle locations, and passable areas, forming a spatial structure representation of the environment to be maintained.

[0029] In some examples, environmental layout maps can also include semantic information. This involves recording semantic labels such as furniture locations (e.g., sofas, dining tables, beds), carpet areas, and pet activity areas (e.g., litter boxes, pet beds) through manual annotation or automatic recognition using large language models, such as Vision Language Models (VLMs). By adding semantic labels to the environmental layout map, a semantic map of the environment to be maintained can be obtained, facilitating the implementation of differentiated environmental maintenance strategies for different types of areas. For example, areas around litter boxes typically have a high frequency of contamination, areas under dining tables are prone to food scraps after meals, and entryway areas are prone to water accumulation during rainy days.

[0030] S220: Map historical pollution events that occurred in the environment to be maintained to the environmental layout map to obtain the historical pollution areas in the environment to be maintained and the pollution patterns corresponding to the historical pollution areas.

[0031] In some examples, historical contamination events refer to contamination events detected and recorded by cleaning equipment during past cleaning tasks. Historical contamination events may include information such as the type of contamination event, the location coordinates of the contaminated area, the contaminated area, the time of occurrence, and the weather conditions at the time of occurrence.

[0032] In some examples, pollution patterns refer to regular information reflecting the characteristics of pollution occurrence in the environment to be maintained, obtained from statistical analysis of historical pollution events.

[0033] In some examples, pollution patterns include at least one of the following: pollution type patterns, pollution frequency patterns, pollution weather patterns, and pollution time patterns. Pollution type patterns reflect the types of pollutants that frequently occur in different areas, such as particulate pollution (e.g., cat litter, food scraps), liquid pollution (e.g., water stains, beverages), and adhesive pollution (e.g., vomit, pet excrement). Pollution frequency patterns reflect the frequency of pollution events occurring in different areas per unit of time. Pollution weather patterns reflect the probability of pollution events occurring under different weather conditions. Pollution time patterns reflect the probability of pollution events occurring at different times of the day.

[0034] In one implementation, historical pollution events are mapped onto an environmental layout map. Specifically, the location of each historical pollution event is marked on the corresponding coordinates of the environmental layout map. By accumulating and marking a large number of historical pollution events, a distribution map of historically polluted areas in the environment to be maintained is formed. Here, a historically polluted area refers to an area in the environment to be maintained where pollution events have occurred in the past. By statistically analyzing the attribute information (such as type, time, weather, etc.) of historical pollution events occurring in each historically polluted area, the pollution patterns corresponding to that area can be determined.

[0035] S230: Generate environmental maintenance strategies for the environment to be maintained based on pollution patterns.

[0036] In some examples, an environmental maintenance strategy refers to a set of maintenance actions for the environment to be maintained. An environmental maintenance strategy includes at least one of a cleaning strategy and an inspection strategy. A cleaning strategy refers to the cleaning parameters and procedures set for different historically contaminated areas. A cleaning strategy may include parameters such as cleaning frequency, cleaning sequence, and cleaning intensity. An inspection strategy refers to the inspection parameters and procedures set for different historically contaminated areas. An inspection strategy may include parameters such as inspection frequency, inspection routes, and observation frequency.

[0037] In one implementation, the cleaning equipment can dynamically adjust the maintenance frequency of different areas according to the pollution frequency pattern, such as increasing the maintenance frequency for high-frequency pollution areas; it can dynamically adjust the cleaning method of different areas according to the pollution type pattern, such as configuring a targeted roller brush cleaning mode for high-frequency hair areas; it can schedule temporary maintenance tasks in specific time periods according to the pollution time pattern, such as performing temporary cleaning of the dining table area after dinner; and it can trigger temporary maintenance tasks under specific weather conditions according to the pollution weather pattern, such as performing temporary water absorption cleaning of the entryway area on rainy days.

[0038] The technical solution provided in this disclosure acquires an environmental layout map of the environment to be maintained, maps historical pollution events onto the environmental layout map to obtain historical pollution areas and their pollution patterns, and generates environmental maintenance strategies based on these patterns. This method combines accumulated data from historical pollution events with a spatial map to achieve long-term learning and memorization of the environment to be maintained. This enables cleaning equipment to identify high-frequency pollution areas, predict pollution trends, and dynamically generate targeted environmental maintenance strategies, thereby improving the cleaning efficiency and intelligence level of the cleaning equipment and ensuring the accuracy of maintenance in high-frequency pollution areas and the rationality of maintenance resource allocation.

[0039] Figure 3 This is a flowchart illustrating step S220 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure. Figure 2 Based on the illustrated embodiment, step S220 may include the following steps.

[0040] S221: Perform event analysis on historical pollution events that occurred within the environment to be maintained, and obtain the historical pollution information corresponding to the historical pollution events.

[0041] In some examples, event parsing refers to the process of extracting parameterized information from stored historical pollution event records. Historical pollution information refers to parameterized information parsed from historical pollution events that describes the characteristics of the pollution events.

[0042] In some examples, historical pollution information includes the coordinates of the pollution location and the area of ​​pollution. The pollution location coordinates are used to indicate the specific location where the pollution event occurred, for example, they can be represented by coordinate values ​​(x, y) in the global coordinate system of the environment to be maintained.

[0043] In one implementation, the coordinates of the contamination location can be calculated by the cleaning equipment based on its own positioning system and sensor data when it detects a contamination event.

[0044] In some examples, the contaminated area is used to represent the extent of the area covered by a contamination event, for example, it can be expressed in square meters (m²). 2The area of ​​contamination is expressed in units of ( ). The contaminated area can be estimated by the cleaning equipment using the bounding box or mask image output by the locally deployed object detection model. For example, the cleaning equipment can use an object detection model (such as a YOLO model or a segmentation network model) to detect pollutants in the environmental images collected by the sensor unit, obtain the bounding box coordinates of the pollutants, and then estimate the contaminated area based on the bounding box size and the actual spatial proportion.

[0045] S222: Divide the environment layout map into a map grid.

[0046] In some examples, a map grid refers to a gridded map formed by dividing an environmental layout map into multiple grid units according to preset rules.

[0047] In one implementation, the environmental layout map can be divided into a uniform N×M grid, where each grid cell (Grid(x, y)) corresponds to a sub-region in the environment to be maintained. The purpose of gridding is to discretize the continuous two-dimensional space, facilitating independent pollution event statistics and analysis for each sub-region.

[0048] In one implementation, the size of the grid cells can be set according to the area of ​​the environment to be maintained and the sensor accuracy of the cleaning equipment. For example, for a home environment, the grid cells can be set to 0.5m × 0.5m or 1m × 1m. The fineness of the grid division affects the accuracy of subsequent contaminated area determination; the finer the grid, the more accurate the contaminated area is located, but the more computing and storage resources are required. The grid cell division size of this disclosure can be customized according to the actual environment and can also be adjusted in real time according to user needs. This disclosure does not impose specific limitations on the numerical value of the grid cell division size.

[0049] S223: Based on the positional relationship between the pollution location coordinates and the map grid, and the coverage of the pollution area with the map grid, determine the historical pollution area corresponding to the historical pollution event.

[0050] In some examples, a historical contamination area refers to a set of map grids covered by historical contamination events.

[0051] In one implementation, the grid cell to which the pollution location coordinates belong can be determined as the core grid of the historical pollution area, and adjacent grid cells partially or completely covered by the pollution area can also be included in the historical pollution area based on the coverage of the pollution area.

[0052] For example, the cleaning equipment can calculate the overlap ratio (coverage) between the contaminated area and each map grid. When the coverage exceeds a preset threshold (e.g., 30%), the map grid is identified as part of a historical contaminated area. In this way, accurate historical contaminated areas can be determined based on the actual impact range of the contamination event.

[0053] S224: Based on historical pollution information, determine the pollution patterns corresponding to historically polluted areas.

[0054] In some examples, cleaning equipment can collect historical pollution information corresponding to all historical pollution events that occurred in each historically polluted area within a historical period, and analyze the distribution patterns of pollution types, frequencies, times, weather, and other dimensions based on the historical pollution information, thereby obtaining the pollution patterns of that historically polluted area.

[0055] The technical solution provided in this disclosure obtains structured historical pollution information by performing event parsing on historical pollution events. It then divides the environmental layout map into a grid, determines historical pollution areas based on pollution location coordinates and pollution area coverage, and identifies pollution patterns based on historical pollution information. This achieves accurate mapping from historical pollution event data to gridded pollution areas and effective extraction of pollution patterns from historical pollution information. The gridded mapping method makes the boundaries of pollution areas more precise, effectively distinguishing different pollution characteristics of adjacent areas. This provides a data foundation for the generation of subsequent differentiated environmental maintenance strategies, thereby improving the targeting and effectiveness of environmental maintenance strategies.

[0056] In some examples, historical pollution information may also include at least one of the following: pollution type, time of pollution occurrence, and weather conditions at the time of pollution occurrence. Pollution type refers to the type of pollutant involved in the pollution event, as described in the foregoing embodiments, and will not be repeated here.

[0057] In one implementation, the cleaning device can also semantically label contaminants, such as hair, cat litter, liquid, and food scraps, to facilitate rapid classification of contaminant types based on semantic understanding. For example, cat litter and food scraps can be quickly classified as particulate contaminants.

[0058] In some examples, the time of pollution occurrence refers to the timestamp when the pollution event was detected. The weather at the time of pollution occurrence refers to the external weather conditions at the time the pollution event occurred, such as sunny, rainy, or cloudy.

[0059] Figure 4 This is a flowchart illustrating step S224 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure.

[0060] like Figure 4 As shown, in Figure 3 Based on the illustrated embodiment, step S224 may include at least one of the following steps S2241-S2244.

[0061] S2241: Based on historical pollution information, statistically analyze the pollution types of historical pollution events that occurred in historically polluted areas, and determine the pollution type patterns of historically polluted areas based on the statistical results.

[0062] In some examples, cleaning equipment can determine the predominant pollution type in a historically polluted area by counting the number of pollution events of each type within an observation period, based on pollution types in historical pollution information. For instance, if the area near a litter box has the highest proportion of litter-related pollution events among multiple historical pollution events occurring in the past month, then the pollution type pattern for that area is "high-incidence area of ​​litter-related pollution." Similarly, if the area near a sofa has the highest proportion of hair-related pollution events among multiple historical pollution events occurring in the past month, then the pollution type pattern for that area is "high-incidence area of ​​hair-related pollution."

[0063] In some examples, pollution type patterns can also include correlations between different pollution types. For instance, in kitchen areas, liquid contamination and food residue contamination may be correlated, with liquid spills increasing the probability of food residue adhesion. Large language models can analyze these cross-type correlation patterns based on historical pollution events, providing a concrete basis for generating comprehensive environmental maintenance strategies.

[0064] S2242: Based on historical pollution information, count the number of times historical pollution events occur in historically polluted areas within a predetermined counting period, and determine the pollution frequency pattern of historically polluted areas based on the statistical results.

[0065] In some examples, the predetermined counting period refers to the time window for frequency statistics, which can be set according to actual needs, such as daily, weekly, or monthly. Pollution frequency patterns reflect the frequency of pollution events occurring in a specific historically polluted area.

[0066] In one implementation, the cleaning equipment can use a weekly counting period to count the number of pollution events occurring weekly in each historically polluted area based on the frequency of pollution events in historical pollution information. If the average number of pollution events occurring in a certain area per week is high (e.g., the number of occurrences exceeds a preset high-frequency threshold), then that area is designated as a "high-frequency pollution area." For example, taking a preset high-frequency threshold of 10 occurrences per week as an example, if the area near the litter box experiences an average of more than 8 litter pollution events per week and an average of more than 6 liquid pollution events per week, totaling an average of 14 pollution events per week, which exceeds the preset high-frequency threshold, then the cleaning equipment can mark the area near the litter box as a high-frequency pollution area.

[0067] If the average number of pollution events occurring in a certain area per week is low (e.g., below a preset low-frequency threshold), then that area is designated as a "low-frequency pollution area." For example, if the preset low-frequency threshold is an average of 3 times per week, and the bedroom area experiences an average of 1-2 pollution events per week, which is less than the preset low-frequency threshold, then the cleaning equipment can mark the bedroom area as a low-frequency pollution area. By analyzing the patterns of pollution frequency, data can be provided to dynamically adjust subsequent inspection and cleaning frequencies. This means increasing maintenance frequency in high-frequency pollution areas and decreasing maintenance frequency in low-frequency pollution areas, thereby achieving rational resource allocation.

[0068] In one implementation approach, pollution frequency patterns can also include frequency change trends. For example, if the pollution frequency in a certain area has been increasing over the past three months, cleaning equipment should increase its maintenance frequency in that area in advance. Through trend analysis, early warning and proactive prevention of pollution risks can be achieved.

[0069] S2243: Based on historical pollution information, statistically analyze the frequency of historical pollution events at different times, and determine the pollution time pattern of historically polluted areas based on the statistical results.

[0070] In some examples, pollution temporal patterns refer to the patterns in which the probability of pollution events occurring in a specific historically polluted area changes over time.

[0071] In one implementation, a day can be divided into multiple time periods (e.g., morning, forenoon, afternoon, evening, night, etc.), and the number of historical pollution events occurring in each time period can be counted to determine the high-incidence periods of pollution in the area.

[0072] It should be noted that the above division of time periods is merely an illustrative example. Users can change the rules for dividing time periods according to their actual needs, for example, dividing them in hours. This disclosure does not specifically limit the rules for dividing time periods.

[0073] In one implementation, cleaning equipment can statistically analyze the frequency of historical pollution events at different times based on the time of pollution occurrence in historical pollution information. For example, statistical analysis might reveal that the area under the dining table experiences a significantly higher frequency of pollution events during dinner time (e.g., 6:00 PM - 8:00 PM) than at other times, primarily due to an increase in food residue-related pollution events. This indicates a "high incidence of pollution after dinner" pattern for this area. Based on this pattern, environmental maintenance strategies can trigger temporary maintenance tasks as the high-incidence pollution period approaches, performing cleaning before or immediately after pollution occurs, effectively reducing the spread and secondary pollution of contaminants in the environment to be maintained.

[0074] S2244: Based on historical pollution information, statistically analyze the frequency of historical pollution events under different weather conditions, and determine the pollution weather patterns in historically polluted areas based on the statistical results.

[0075] In some examples, the pattern of polluted weather refers to the pattern in which the probability of pollution events in a specific historically polluted area changes with external weather conditions.

[0076] In one implementation method, weather conditions can be categorized into sunny, cloudy, rainy, and snowy days, and the number of historical pollution events under each weather condition can be counted to determine the high-incidence weather conditions for pollution in the region.

[0077] In some examples, cleaning equipment can statistically analyze the frequency of historical pollution events under different weather conditions based on the weather when pollution occurred in historical pollution information. For instance, if the frequency of water accumulation in the entryway area is significantly higher on rainy days than on sunny days, then the pollution weather pattern in the entryway area is "high incidence of pollution on rainy days." Similarly, the frequency of dust accumulation in the balcony area is higher under windy and sandy weather conditions.

[0078] In some examples, based on the patterns of polluted weather, control equipment can obtain real-time weather data through a network interface. When it detects that the current weather conditions match the high-incidence weather conditions of a certain area, it can proactively trigger temporary inspection or cleaning tasks in that area, thereby achieving preventive environmental maintenance based on weather forecasts.

[0079] The technical solution provided in this disclosure statistically analyzes historical pollution information from multiple dimensions such as pollution type, pollution frequency, pollution time, and pollution weather, and determines the patterns of pollution type, pollution frequency, pollution time, and pollution weather, thereby achieving multi-dimensional analysis of the pollution patterns of historical pollution events. This enables environmental maintenance strategies to be supported by multi-dimensional data under various conditions, and improves the intelligence level and cleaning efficiency of cleaning equipment.

[0080] In some examples, historical pollution information also includes historical maintenance strategies and historical maintenance results, which indicate whether the preset requirements were met or not.

[0081] Figure 5 This is a schematic diagram of the first step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure.

[0082] like Figure 5 As shown above, in the above Figure 3 Based on the illustrated embodiment, step S230 may include the following steps: S231: If the historical maintenance results do not meet the preset requirements, generate an environmental maintenance strategy for the environment to be maintained based on the historical maintenance strategy.

[0083] In some examples, historical maintenance strategies refer to environmental maintenance plans adopted in response to historical pollution events. Historical maintenance strategies may include cleaning strategy parameters (such as cleaning frequency, cleaning mode, etc.) and / or inspection strategy parameters (such as inspection frequency, inspection route, etc.).

[0084] In some examples, historical maintenance results refer to the effectiveness evaluation results after implementing historical maintenance strategies. The effectiveness of maintenance can be judged by conducting a secondary inspection of the area after the cleaning equipment performs the maintenance task.

[0085] Preset requirements refer to the standards by which maintenance results achieve the expected goals, such as the complete cleaning of contaminated areas or the residual area of ​​pollutants falling below a preset threshold. If historical maintenance results do not meet the preset requirements, it indicates that the historical maintenance strategy was effective for the area, and therefore the current environmental maintenance strategy can be directly generated based on the historical maintenance strategy.

[0086] In one implementation, if the historical maintenance results do not meet the preset requirements, the cleaning equipment can generate an environmental maintenance strategy for the environment to be maintained based on the historical maintenance strategy, so that the environmental maintenance strategy can also enable the current maintenance results to meet the preset requirements.

[0087] In another implementation, when generating an environmental maintenance strategy for the environment to be maintained based on historical maintenance strategies, the cleaning equipment can also make fine-tuning adjustments to suit the current situation. For example, if the current contaminated area is larger than the historical contaminated area, the cleaning intensity can be appropriately increased or the cleaning time extended based on the historical maintenance strategy. If new furniture or obstacles are added to the current area, the inspection route can be adjusted accordingly. This approach retains the reuse of effective strategies while adapting to changes in the environment.

[0088] S232: If the historical maintenance results show that the preset requirements have not been met, the environmental maintenance strategy for the environment to be maintained shall be updated based on the pollution patterns and historical maintenance strategies.

[0089] In another example, if the historical maintenance result is that the preset requirements are not met, it means that the original historical maintenance strategy is not effective and needs to be adjusted and optimized. In this case, the cleaning equipment can update the environmental maintenance strategy of the environment to be maintained based on the pollution pattern and the historical maintenance strategy.

[0090] In one implementation, updating the environmental maintenance strategy can include: analyzing the reasons for maintenance failures, such as insufficient cleaning intensity, inadequate inspection frequency, or cleaning modes unsuitable for the current type of pollution; and then adjusting relevant parameters in the maintenance strategy based on pollution patterns and failure causes. For example, if the analysis reveals that the cleaning failure in the litter area is due to the low rotation speed of the actuator's roller brush, resulting in the litter not being completely sucked into the dustbin, the roller brush speed can be increased; if the analysis reveals that the cleaning failure in the entryway area due to water accumulation is due to the actuator's water suction function not being activated, an instruction to activate the water suction function can be added to the entryway area's maintenance strategy.

[0091] In one implementation, the process of updating environmental maintenance strategies can utilize a large language model for intelligent analysis. Historical maintenance strategies, historical maintenance results, and current pollution patterns are input into the large language model. Based on semantic understanding, the large language model can analyze the reasons for maintenance failures and generate updated maintenance strategy parameters. For example, the large language model can output updated behavioral state machine parameters, including the states of the roller brush, mopping, water pump, suction mode, and travel speed, to finely control the cleaning equipment to perform the updated maintenance behaviors.

[0092] The technical solution provided in this disclosure achieves adaptive optimization and closed-loop feedback of environmental maintenance strategies by directly reusing effective historical maintenance strategies when the historical maintenance results do not meet the preset requirements, and updating the strategies based on pollution patterns and historical maintenance strategies when the preset requirements are not met. This enables cleaning equipment to have the ability to learn and continuously improve itself, gradually enhancing the autonomous decision-making ability and long-term operating effect of the cleaning equipment, thereby solving the problem that existing cleaning equipment cannot continuously update its strategies based on historical maintenance results.

[0093] Figure 6 This is a second flowchart illustrating step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure.

[0094] like Figure 6 As shown, in Figure 2 Based on the illustrated embodiment, step S230 may include the following steps: S233: Based on the pollution pattern, obtain the pollution frequency of the environment to be maintained, and when the pollution frequency is higher than the preset high-frequency threshold, determine that the environment to be maintained is a high-frequency pollution area.

[0095] In some examples, cleaning equipment can obtain the pollution frequency from the pollution frequency pattern in the pollution pattern.

[0096] A preset high-frequency threshold is a frequency boundary value used to distinguish between high-frequency pollution areas and ordinary pollution areas, and can be set according to actual needs. For example, the preset high-frequency threshold can be set to an average of 10 occurrences per week. When the pollution frequency is higher than the preset high-frequency threshold, the environment to be maintained is identified as a high-frequency pollution area. For example, when the average number of pollution events in a certain area exceeds 10 per week, that area is identified as a high-frequency pollution area. High-frequency pollution areas typically correspond to areas with concentrated pollution events that require special attention and maintenance, such as around cat litter boxes, entryways, and under dining tables.

[0097] In one implementation, the preset high-frequency threshold is not fixed and can be dynamically adjusted based on the overall pollution level of the environment to be maintained. For example, during seasonal changes, increased pet shedding may raise the overall environmental pollution frequency. In this case, the preset high-frequency threshold can be appropriately increased to prevent too many areas from being marked as high-frequency polluted areas, thus avoiding excessive dispersion of maintenance resources. As another example, during holidays, increased indoor activity may cause a temporary increase in pollution frequency in some areas. The system can dynamically adjust the threshold based on short-term trends, making the identification of high-frequency polluted areas more flexible and accurate.

[0098] S234: Generate environmental maintenance strategies for high-frequency pollution areas.

[0099] After the cleaning equipment identifies high-frequency pollution areas, an environmental maintenance strategy can be generated for these areas. This strategy maintains these high-frequency pollution areas at a higher frequency than a preset maintenance frequency. The preset maintenance frequency refers to the standard frequency for performing environmental maintenance on ordinary areas, such as once a week.

[0100] For areas with high-frequency pollution, the generated maintenance strategy should increase the maintenance frequency to a level greater than the preset frequency, such as once a day or once every half day. The specific increase in maintenance frequency can be determined based on the pollution frequency value; the higher the pollution frequency, the greater the increase in maintenance frequency.

[0101] In one implementation, when the cleaning equipment generates an environmental maintenance strategy for high-frequency contamination areas, it can also simultaneously adjust the inspection strategy. For example, the inspection frequency for high-frequency contamination areas can be increased, allowing the cleaning equipment to access these areas more frequently and detect their contamination status during its patrols.

[0102] In addition, the cleaning equipment can adjust its inspection route, setting high-frequency contamination areas as priority access nodes on the route to ensure that the cleaning equipment covers high-frequency contamination areas first in each inspection task. For extremely high-frequency contamination areas (such as areas where the contamination frequency exceeds a preset extremely high threshold), a dedicated inspection mode can also be configured, in which the cleaning equipment performs independent inspection and cleaning tasks on the area in addition to regular cleaning tasks.

[0103] In one implementation, the maintenance strategy for high-frequency contamination areas may also include adjusting the frequency of observation activities. Observation activities refer to the actions of cleaning equipment in non-contactly detecting the contamination status of an area using sensors (such as RGB cameras). For high-frequency contamination areas, the frequency of observation activities can be increased, enabling the cleaning equipment to proactively perform image acquisition and contamination detection each time it approaches the area, in order to promptly detect new contamination events and trigger cleaning tasks.

[0104] The technical solution provided in this disclosure identifies high-frequency pollution areas based on pollution frequency and generates environmental maintenance strategies for high-frequency pollution areas with maintenance frequencies greater than preset maintenance frequencies. This enables dynamic allocation of maintenance resources, allowing high-frequency pollution areas to receive higher-frequency maintenance, thereby improving the maintenance efficiency of high-frequency pollution areas and the rationality of maintenance resource allocation.

[0105] Figure 7 This is a schematic diagram of the third step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure.

[0106] like Figure 7 As shown, in Figure 2 Based on the illustrated embodiment, step S230 may include the following steps: S235: Based on the pollution pattern, obtain the pollution frequency of the environment to be maintained, and when the pollution frequency is lower than the preset low-frequency threshold, determine the environment to be maintained as a low-frequency pollution area.

[0107] The method for obtaining the pollution frequency can be found in the aforementioned embodiments, and will not be repeated here.

[0108] A preset low-frequency threshold is a frequency boundary value used to distinguish between low-frequency pollution areas and ordinary pollution areas. When the pollution frequency is lower than the preset low-frequency threshold, the environment to be maintained is identified as a low-frequency pollution area. For example, the preset low-frequency threshold can be set to an average of 3 times per week. When the average number of pollution events in a certain area is less than 3 times per week, that area is identified as a low-frequency pollution area. Low-frequency pollution areas typically correspond to areas where pollution events occur very rarely and routine maintenance can meet cleaning needs, such as guest rooms, storage rooms, and other indoor spaces with low usage frequency.

[0109] S236: Generate environmental maintenance strategies for low-frequency pollution areas.

[0110] For low-frequency pollution areas, the generated maintenance strategy should reduce the maintenance frequency to a level lower than the preset maintenance frequency, such as once every two weeks or once a month. By reducing the maintenance frequency in low-frequency pollution areas, the saved maintenance resources (such as electricity, time, consumables, etc.) can be allocated to high-frequency pollution areas, so as to focus on the maintenance effectiveness in high-frequency pollution areas.

[0111] In one implementation, the maintenance strategy for low-frequency contamination areas can also include reducing the frequency of inspections. During regular patrols, cleaning equipment can reduce its access frequency to low-frequency contamination areas, or set the inspection priority of low-frequency contamination areas to the lowest level, placing them at the end of its patrol route planning. This reduces the time spent by the cleaning equipment in low-frequency contamination areas, allowing more time to be devoted to the maintenance of high-frequency contamination areas.

[0112] The technical solution provided in this disclosure identifies low-frequency pollution areas based on pollution frequency and generates environmental maintenance strategies for low-frequency pollution areas with maintenance frequencies lower than preset maintenance frequencies. This allows the saved resources to be concentrated on the maintenance of high-frequency pollution areas, thereby improving the maintenance efficiency for high-frequency pollution areas and the resource utilization rate of cleaning equipment.

[0113] Figure 8 This is a schematic diagram of the fourth step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure.

[0114] like Figure 8 As shown, in Figure 2 Based on the illustrated embodiment, step S230 may include the following steps: S237: Based on the pollution patterns, determine the type of pollution in the environment to be maintained.

[0115] In some examples, cleaning equipment can determine the type of pollution in the environment to be maintained from the pollution type pattern in the pollution pattern.

[0116] In one implementation, an area may correspond to multiple main pollution types. For example, a kitchen area may simultaneously contain liquid pollution (water stains, oil stains) and solid particulate pollution (food residue). Based on this, an environmental maintenance strategy for a specific area (kitchen area) can be generated by combining one or more main pollution types.

[0117] S238: Generate an environmental maintenance strategy for the environment to be maintained based on a preset mapping relationship between pollution type and cleaning strategy and / or a preset mapping relationship between pollution type and inspection strategy.

[0118] In some examples, the preset mapping relationship refers to the pre-established correspondence between pollution types and cleaning strategy parameters and / or inspection strategy parameters. Different pollution types have different requirements for the cleaning strategy parameters of the cleaning equipment. For example: hair pollution requires the roller brush to be turned on and run at a high speed to roll the hair into the dust box; liquid pollution requires the roller brush to be turned off to prevent the roller brush from spreading the liquid and causing secondary pollution, the water pump to be turned off to prevent further increase in humidity, and the water suction mode to be turned on to suck the liquid into the wastewater tank; particulate pollution (such as cat litter) requires the roller brush to be turned on and run at a standard speed to ensure that the particles are effectively sucked in; adhesive pollution (such as vomit) requires the roller brush to be turned off, mopping to be turned off, the travel speed to be reduced, and a detour strategy to enter the polluted area to avoid the pollutants adhering to the equipment and causing secondary pollution, etc.

[0119] In one implementation, the inspection strategy parameters for cleaning equipment differ depending on the type of contamination. For example, for areas with high incidence of hair-type contamination, the inspection strategy may include increasing the image acquisition frequency of the visual sensor, while also using an infrared camera for detection in low-light environments; for areas with high incidence of adhesive-type contamination, the inspection strategy may include increasing the sensitivity of image detection during inspection to detect small areas of adhesive contamination as early as possible.

[0120] The cleaning equipment can generate different environmental maintenance strategies (cleaning strategies and inspection strategies) for different areas based on preset mapping relationships and the types of pollution corresponding to those areas. These strategies are then aggregated to obtain the environmental maintenance strategy for the environment to be maintained. For example, for the type of hair in the litter box area, a cleaning strategy of turning on the roller brush and running it at a high speed is used, along with an inspection strategy that increases the image acquisition frequency of the visual sensor and uses an infrared camera for detection in low-light environments.

[0121] The above is merely an illustrative example of different pollution types corresponding to different regions. In real-world scenarios, the corresponding cleaning and inspection strategies can be determined in the mapping relationship based on the pollution type to generate the environmental maintenance strategy for that region. This is not limited here.

[0122] The technical solution provided in this disclosure generates environmental maintenance strategies based on a preset mapping relationship between pollution types and cleaning and / or inspection strategies, thereby achieving differentiated maintenance for different pollution types. Each pollution type can obtain a corresponding cleaning and inspection mode, improving the adaptability and compatibility of maintenance for different pollution types.

[0123] Figure 9 This is a schematic diagram of the fifth step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure.

[0124] like Figure 9 As shown, in Figure 2 Based on the illustrated embodiment, step S230 may include the following steps: S239: Based on pollution patterns, obtain the weather triggering conditions for the environment to be maintained.

[0125] In some examples, weather triggering conditions refer to weather conditions that can trigger the generation or adjustment of environmental maintenance strategies.

[0126] In one implementation, cleaning equipment can derive weather triggering conditions from pollution patterns. For example, by analyzing the pollution weather patterns in the entryway area, it can be found that the probability of water accumulation in this area is significantly higher on rainy days than on non-rainy days; therefore, "the current weather is rainy" can be determined as the weather triggering condition for this area. Similarly, by analyzing the pollution weather patterns in the balcony area, it can be found that the probability of dust deposition is higher on windy and dusty days; therefore, "the current weather is windy and dusty" can be determined as the weather triggering condition for this area.

[0127] In one implementation, weather triggering conditions are not limited to a single weather condition, but can also be a combination of multiple weather conditions or a weather change trend. For example, "two consecutive days of rainfall" or "the weather changing from sunny to cloudy and rainy" can be used as weather triggering conditions to more accurately reflect the actual impact of weather changes on the state of environmental pollution.

[0128] S2310: Obtain the current weather and, if the current weather meets the weather triggering conditions, determine that the environment to be maintained is a weather-polluted area.

[0129] In some examples, current weather refers to real-time external weather conditions.

[0130] In one implementation, the control device can access a meteorological service platform via a network interface, such as the China Meteorological Administration's Application Programming Interface (API) or a third-party meteorological data service, to obtain real-time weather data for the current location, including weather type (sunny, cloudy, rainy, snowy, etc.), temperature, humidity, wind speed, and other information.

[0131] The control equipment then matches the acquired current weather with weather triggering conditions. If the current weather meets the weather triggering conditions, the control equipment identifies the environment to be maintained as a weather-polluted area. A weather-polluted area refers to a region where the frequency of pollution increases due to changes in weather conditions.

[0132] S2311: Generate environmental maintenance strategies for areas with weather pollution.

[0133] In some examples, after identifying a weather-polluted area, the cleaning equipment can generate an environmental maintenance strategy corresponding to that area. This strategy includes setting temporary maintenance tasks for the polluted area. Temporary maintenance tasks refer to environmental maintenance tasks added temporarily outside of regular maintenance tasks. These can include temporary cleaning tasks, such as performing temporary water-absorbing cleaning on the entryway area; and temporary inspection tasks, such as performing a temporary inspection of the entrance floor to check for dampness or pollution. Temporary maintenance tasks can be executed when weather trigger conditions are met, or within a preset time window after a weather change (e.g., within 30 minutes after the rain stops).

[0134] In one implementation, the specific parameters of temporary maintenance tasks can be customized based on weather conditions and regional characteristics. For example, for a temporary maintenance task in the entryway triggered by rain, it can be configured to turn off the roller brush, turn on the water suction mode, and pass through at a low speed to prevent water stains from spreading to other areas. For a temporary maintenance task on the balcony triggered by windy and sandy weather, it can be configured to turn on the roller brush and increase suction power to effectively remove sand and dust. For a temporary inspection task triggered by snowy weather, it can be configured to increase the image acquisition frequency of the visual sensor in the entrance area to promptly detect liquid pollution caused by melting snow.

[0135] In one implementation, once a temporary maintenance task is generated, it can be inserted into the current task queue of the cleaning equipment, and its priority can be adjusted according to the urgency. For example, if the current weather is heavy rain and water accumulation or stains have been detected in the entryway area, the temporary maintenance task should be set to the highest priority, thereby interrupting the current cleaning task and executing the temporary maintenance task instead; if the current weather is only light rain and no pollution has been detected in the entryway area, the temporary maintenance task can be placed at the end of the task queue and executed after the current area is cleaned.

[0136] The technical solution provided in this disclosure obtains weather triggering conditions based on the pattern of polluted weather, acquires the current weather, and generates an environmental maintenance strategy including temporary maintenance tasks when the conditions are met. This enables weather-adaptive adjustment of the environmental maintenance strategy, allowing cleaning equipment to change the environmental maintenance strategy based on changes in weather conditions. This allows for timely cleaning of environmental pollution caused by weather factors, improving the timeliness and preventative nature of environmental maintenance.

[0137] Figure 10 This is a schematic diagram of the sixth step S230 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure.

[0138] like Figure 10 As shown above, in the aforementioned Figure 2 Based on the illustrated embodiment, step S230 may include the following steps: S2312: Based on the pollution patterns, obtain the high-frequency pollution times of the environment to be maintained.

[0139] In some examples, high-frequency contamination time refers to the period of time in a particular environment to be maintained where the probability of contamination events is higher than at other times.

[0140] In one implementation, cleaning equipment can directly obtain high-frequency pollution times from the pollution time patterns. For example, analysis of historical pollution data in the area under the dining table reveals that food residue contamination occurs several times more frequently during dinner time (6:00 PM - 8:00 PM) than at other times, thus identifying "6:00 PM - 8:00 PM" as the high-frequency pollution time for that area. Similarly, analysis of historical pollution data around the litter box reveals that pets are more likely to use the litter box after eating in the morning (6:00 AM - 8:00 AM) and evening (5:00 PM - 7:00 PM), making these two time periods peak times for litter litter contamination.

[0141] In one implementation, the high-frequency pollution time may vary with factors such as seasons and user lifestyles. Therefore, historical pollution data can be re-analyzed periodically (e.g., monthly) to update the high-frequency pollution time of each region and ensure that the pollution time pattern is synchronized with the actual pollution situation.

[0142] S2313: Generate environmental maintenance strategies for the environment to be maintained based on the high-frequency pollution time.

[0143] In some examples, after acquiring the high-frequency contamination time, the cleaning equipment can generate an environmental maintenance strategy corresponding to the environment to be maintained. The environmental maintenance strategy includes setting temporary maintenance tasks for the environment to be maintained during the high-frequency contamination time.

[0144] In one implementation, the temporary maintenance tasks set for the environment to be maintained during high-frequency pollution periods can be either preventative inspections performed before the start of the high-frequency pollution period or targeted cleaning tasks performed after the high-frequency pollution period ends. For example, before dinner time (6:00 PM), the cleaning equipment can perform a pre-cleaning of the area under the dining table to remove any contaminants that may remain from the previous meal; after dinner time ends (8:00 PM), the cleaning equipment can perform a cleaning of the area under the dining table to remove any newly generated food scraps, etc.

[0145] In one implementation, the timing of temporary maintenance tasks can be flexibly configured according to actual needs. For example, for the area around the litter box, temporary maintenance tasks can be configured to be performed after the pets finish eating, because the probability of litter scattering is highest at this time.

[0146] In one implementation, the cleaning equipment can be configured with independent high-frequency contamination times and corresponding temporary maintenance tasks for different areas. The equipment can automatically generate a task plan containing multiple temporary maintenance tasks by matching the current time with the configuration of each area. When multiple temporary maintenance tasks overlap in time, they can be prioritized based on the degree of contamination in each area and the urgency of the task, ensuring that the area most in need of maintenance receives priority service. Simultaneously, the frequency and scope of temporary maintenance tasks can be adaptively adjusted based on the cleaning equipment's own resource conditions, such as remaining battery power, to avoid insufficient battery power due to frequent execution of temporary maintenance tasks, preventing the equipment from completing subsequent tasks.

[0147] The technical solution provided in this disclosure obtains high-frequency pollution times based on pollution time patterns and sets temporary maintenance tasks during high-frequency pollution times, enabling cleaning equipment to automatically adjust maintenance according to pollution time patterns. This allows maintenance tasks to be performed promptly before and after periods of high pollution incidence, achieving a response to environmental pollution times and effectively reducing the residence time of pollutants in the environment to be maintained, thereby improving the maintenance response speed and cleaning effect of the cleaning equipment.

[0148] Figure 11 This is a flowchart illustrating the process before step S220 of an environmental maintenance strategy generation method provided in an exemplary embodiment of this disclosure.

[0149] like Figure 11 As shown, in Figure 2 Based on the illustrated embodiment, the following steps may be included before step S220: S225: For maintenance tasks performed on contaminated areas within an environment to be maintained, after the maintenance task is completed, record the pollution information and environmental information of the contaminated area, as well as the task information of the maintenance task.

[0150] In some examples, a maintenance task refers to a cleaning and / or inspection task performed by the cleaning equipment on contaminated areas in the environment to be maintained. After each maintenance task is completed, the cleaning equipment records contamination information and environmental information of the contaminated area, as well as task information of the maintenance task.

[0151] In one implementation, pollution information may include pollution type, pollution location coordinates, pollution area, and pollution occurrence time. The source of pollution information can be pollution detection results collected and analyzed by cleaning equipment through sensors during maintenance tasks. For example, after the cleaning equipment acquires ground images using an RGB camera, it uses a target detection model (such as the YOLO model) to detect pollutants in the images and outputs information such as pollutant type labels, bounding box coordinates, and confidence levels. Then, based on the bounding box coordinates and spatial proportions, it converts these into pollution location coordinates and pollution area.

[0152] In one implementation, environmental information may include weather conditions (e.g., sunny, cloudy, rainy), lighting conditions, temperature, humidity, etc., during the maintenance task. Environmental information can be obtained from meteorological services via a network interface or collected by sensors (e.g., temperature and humidity sensors) integrated into the cleaning equipment itself.

[0153] In one implementation, task information may include maintenance strategy parameters (e.g., cleaning mode, cleaning intensity, inspection route, etc.) and maintenance results (e.g., cleaning success or failure, area of ​​residual contaminants, etc.). The maintenance result can be determined by a secondary inspection of the area by the cleaning equipment after the maintenance task is completed. If the secondary inspection shows that the contaminants have been completely removed, the maintenance result is considered successful; if the secondary inspection shows that contaminants remain, the maintenance result is considered a failure.

[0154] S226: Generate historical pollution events based on pollution information, environmental information, and task information.

[0155] In some examples, cleaning equipment can generate historical pollution events based on pollution information, environmental information, and task information.

[0156] In one implementation, historical pollution events can include the following structured fields: event identifier (Event_ID), pollution type (Pollution_Type), pollution location coordinates (Pollution_Position), pollution area (Pollution_Area), pollution occurrence time (Pollution_Time), weather conditions (Weather), maintenance strategy parameters (Maintenance_Strategy), and maintenance result (Maintenance_Result). Historical pollution events can be stored in the control equipment's database, forming a long-term pollution history database of the environment to be maintained.

[0157] In one implementation, as historical pollution events accumulate, the cleaning equipment can periodically clean and maintain the historical pollution event database, such as deleting expired or invalid records, merging duplicate records, and normalizing the data, to ensure the data quality and consistency of historical pollution events and generate a reliable data source for subsequent pollution pattern analysis and environmental maintenance strategies.

[0158] The technical solution provided in this disclosure records pollution information, environmental information, and task information of the polluted area after each maintenance task is completed, and generates historical pollution events based on this information, thereby achieving the recording and continuous accumulation of the entire historical maintenance process and providing a reliable source of historical pollution event data for the subsequent generation of environmental maintenance strategies.

[0159] Exemplary device Figure 12 This is a schematic diagram of the structure of an environmental maintenance strategy generation device provided in an exemplary embodiment of the present disclosure.

[0160] like Figure 12 As shown, in one embodiment, the environmental maintenance strategy generation device 1200 includes: The acquisition module 1210 is used to acquire the environment layout map corresponding to the environment to be maintained.

[0161] The event mapping module 1220 is used to map historical pollution events that occur in the environment to be maintained to the environmental layout map, so as to obtain the historical pollution areas in the environment to be maintained and the pollution patterns corresponding to the historical pollution areas. The pollution patterns include at least one of the following: pollution type pattern, pollution frequency pattern, pollution weather pattern, and pollution time pattern.

[0162] The strategy generation module 1230 is used to generate an environmental maintenance strategy for the environment to be maintained based on the pollution pattern. The environmental maintenance strategy includes at least one of a cleaning strategy and an inspection strategy.

[0163] In one embodiment, the environmental maintenance strategy generation device 1200 may further include an event recording module for recording historical pollution events.

[0164] In one embodiment, the event logging module is also used to store historical contamination events.

[0165] In this embodiment, the modules or sub-modules of the environmental maintenance strategy generation device can be deployed in the cleaning equipment, the control equipment, or distributed between the cleaning equipment and the control equipment. In other words, the functions implemented by the environmental maintenance strategy generation device can be achieved independently by the cleaning equipment, independently by the control equipment, or jointly by the cleaning equipment and the control equipment; this embodiment does not limit the scope of the application.

[0166] The beneficial technical effects corresponding to the exemplary embodiments of this device can be found in the corresponding beneficial technical effects of the exemplary method section above, and will not be repeated here.

[0167] Exemplary electronic devices Figure 13 This is a structural diagram of an electronic device provided in an embodiment of the present disclosure.

[0168] like Figure 13 As shown, the electronic device 1300 includes at least one processor 1301 and a memory 1302.

[0169] The processor 1301 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 1300 to perform desired functions.

[0170] The memory 1302 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 1301 may execute one or more computer program instructions to implement the environment maintenance strategy generation method and / or other desired functions of the various embodiments of this disclosure described above.

[0171] In one example, the electronic device 1300 may also include an input device 1303 and an output device 1304, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0172] The input device 1303 may also include, for example, a keyboard, a mouse, etc.

[0173] The output device 1304 can output various information to the outside, including, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0174] Of course, for the sake of simplicity, Figure 13 Only some of the components of the electronic device 1300 relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device 1300 may include any other suitable components depending on the specific application.

[0175] Exemplary computer program products and computer-readable storage media In addition to the methods and apparatus described above, embodiments of this disclosure may also provide a computer program product, including computer program instructions that, when executed by a processor, cause the processor to perform the steps in the environment maintenance strategy generation method of the various embodiments of this disclosure described in the "Exemplary Methods" section above.

[0176] Computer program products can be written in any combination of one or more programming languages ​​to perform the operations of embodiments of this disclosure. These programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0177] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions that, when executed by a processor, cause the processor to perform the steps in the environment maintenance strategy generation methods of various embodiments of this disclosure described in the "Exemplary Methods" section above.

[0178] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, but is not limited to, systems, apparatuses, or devices that are electrical, magnetic, optical, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires; portable disks; hard disks; random access memory (RAM); read-only memory (ROM); erasable programmable read-only memory (EPROM); or flash memory; optical fiber; compact disc read-only memory (CD-ROM); optical storage devices; magnetic storage devices; or any suitable combination thereof.

[0179] The basic principles of this disclosure have been described above with reference to specific embodiments. However, the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0180] Various modifications and variations can be made to this disclosure without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, this disclosure is also intended to include such modifications and variations.

Claims

1. A method for generating an environmental maintenance strategy, comprising: Obtain the environment layout map corresponding to the environment to be maintained; Mapping historical pollution events occurring within the environment to be maintained onto the environmental layout map yields historical pollution areas and corresponding pollution patterns within the environment to be maintained. These pollution patterns include at least one of pollution type patterns, pollution frequency patterns, pollution weather patterns, and pollution time patterns. An environmental maintenance strategy for the environment to be maintained is generated based on the pollution pattern, and the environmental maintenance strategy includes at least one of a cleaning strategy and an inspection strategy.

2. The method according to claim 1, wherein, Mapping historical pollution events occurring within the environment to be maintained to the environmental layout map yields historically polluted areas and corresponding pollution patterns within the environment to be maintained, including: Event parsing is performed on historical pollution events that occurred within the environment to be maintained to obtain historical pollution information corresponding to the historical pollution events, wherein the historical pollution information includes pollution location coordinates and pollution area; The environmental layout map is divided into a map grid; Based on the positional relationship between the pollution location coordinates and the map grid, and the coverage of the pollution area with the map grid, the historical pollution area corresponding to the historical pollution event is determined; Based on the historical pollution information, the pollution patterns corresponding to the historically polluted areas are determined.

3. The method according to claim 2, wherein, The historical pollution information also includes at least one of the following: pollution type, time of pollution occurrence, and weather conditions at the time of pollution occurrence. Determining the pollution pattern corresponding to the historically polluted area based on the historical pollution information includes at least one of the following steps: Based on the historical pollution information, the pollution types of the historical pollution events that occurred in the historically polluted area are statistically analyzed, and the pollution type patterns of the historically polluted area are determined based on the statistical results. Based on the historical pollution information, the number of times the historical pollution events occurred in the historical pollution area within a predetermined counting period is counted, and the pollution frequency pattern of the historical pollution area is determined based on the statistical results. Based on the historical pollution information, the frequency of occurrence of the historical pollution events at different times is statistically analyzed, and the pollution time pattern of the historically polluted area is determined according to the statistical results. Based on the historical pollution information, the frequency of occurrence of the historical pollution events under different weather conditions is statistically analyzed, and the pollution weather patterns of the historical pollution areas are determined based on the statistical results.

4. The method according to claim 2, wherein, The historical pollution information also includes historical maintenance strategies and historical maintenance results, wherein the historical maintenance results are either meeting preset requirements or not meeting preset requirements; The environmental maintenance strategy for generating the environment to be maintained based on the pollution pattern includes: If the historical maintenance results do not meet the preset requirements, an environmental maintenance strategy for the environment to be maintained is generated based on the historical maintenance strategy. If the historical maintenance results do not meet the preset requirements, the environmental maintenance strategy for the environment to be maintained is updated based on the pollution patterns and the historical maintenance strategies.

5. The method according to claim 1, wherein, The environmental maintenance strategy for generating the environment to be maintained based on the pollution pattern includes: Based on the pollution pattern, the pollution frequency of the environment to be maintained is obtained, and when the pollution frequency is higher than a preset high-frequency threshold, the environment to be maintained is determined to be a high-frequency pollution area. An environmental maintenance strategy is generated for the high-frequency pollution area, wherein the maintenance frequency of the environmental maintenance strategy for the high-frequency pollution area is greater than a preset maintenance frequency.

6. The method according to claim 1, wherein, The environmental maintenance strategy for generating the environment to be maintained based on the pollution pattern includes: Based on the pollution pattern, the pollution frequency of the environment to be maintained is obtained, and when the pollution frequency is lower than a preset low-frequency threshold, the environment to be maintained is determined to be a low-frequency pollution area. An environmental maintenance strategy is generated for the low-frequency pollution area, wherein the maintenance frequency of the environmental maintenance strategy for the low-frequency pollution area is less than a preset maintenance frequency.

7. The method according to claim 1, wherein, The environmental maintenance strategy for generating the environment to be maintained based on the pollution pattern includes: Based on the pollution patterns, the pollution type of the environment to be maintained is obtained; Based on the preset mapping relationship between the pollution type and the cleaning strategy and / or the preset mapping relationship between the pollution type and the inspection strategy, an environmental maintenance strategy for the environment to be maintained is generated, wherein the environmental maintenance strategy adopts the cleaning strategy and / or the inspection strategy corresponding to the pollution type for different pollution types.

8. The method according to claim 1, wherein, The environmental maintenance strategy for generating the environment to be maintained based on the pollution pattern includes: Based on the pollution pattern, obtain the weather triggering conditions for the environment to be maintained; Obtain the current weather, and if the current weather meets the weather triggering conditions, determine that the environment to be maintained is a weather pollution area; Generate an environmental maintenance strategy corresponding to the weather-polluted area, wherein the environmental maintenance strategy includes setting temporary maintenance tasks for the weather-polluted area.

9. The method according to claim 1, wherein, The environmental maintenance strategy for generating the environment to be maintained based on the pollution pattern includes: Based on the pollution pattern, the high-frequency pollution time of the environment to be maintained is obtained; Based on the high-frequency pollution time, an environmental maintenance strategy corresponding to the environment to be maintained is generated, wherein the environmental maintenance strategy includes setting temporary maintenance tasks for the environment to be maintained during the high-frequency pollution time.

10. The method according to claim 2, wherein, Before mapping historical pollution events occurring within the environment to be maintained to the environmental layout map to obtain the historical pollution areas and corresponding pollution patterns in the environment to be maintained, the process further includes: For maintenance tasks performed on contaminated areas within the environment to be maintained, after the maintenance tasks are completed, the pollution information and environmental information of the contaminated areas, as well as the task information of the maintenance tasks, are recorded. Historical pollution events are generated based on the pollution information, the environmental information, and the task information.

11. An environmental maintenance strategy generation device, comprising: The acquisition module is used to acquire the environment layout map corresponding to the environment to be maintained. The event mapping module is used to map historical pollution events occurring in the environment to be maintained to the environmental layout map, thereby obtaining historical pollution areas in the environment to be maintained and the pollution patterns corresponding to the historical pollution areas. The pollution patterns include at least one of pollution type patterns, pollution frequency patterns, pollution weather patterns, and pollution time patterns. The strategy generation module is used to generate an environmental maintenance strategy for the environment to be maintained based on the pollution pattern. The environmental maintenance strategy includes at least one of a cleaning strategy and an inspection strategy.

12. The apparatus of claim 11 further includes an event recording module, the event recording module being used to record the historical contamination events and to store the historical contamination events.

13. A computer-readable storage medium storing a computer program for executing the environmental maintenance strategy generation method according to any one of claims 1-10.

14. An electronic device comprising: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the environmental maintenance strategy generation method according to any one of claims 1-10.

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