Formaldehyde treatment method and system for indoor environment

Abstract

The invention discloses a formaldehyde treatment method and system for an indoor environment, and relates to the technical field of formaldehyde treatment. The method comprises the following steps: after formaldehyde concentration drift compensation is carried out on perception data of a target indoor space to obtain calibration environment formaldehyde data, three-dimensional discrete mapping is carried out on the calibration environment formaldehyde data to generate a formaldehyde grid space; tracing the release bodies in the formaldehyde grid space to obtain K formaldehyde release bodies; according to the distance-concentration characteristics of the K groups of release associated grids and the K formaldehyde release bodies, carrying out spraying task aggregation to obtain P groups of grid spraying tasks; performing obstacle avoidance compensation on the P groups of grid spraying tasks to obtain P spraying tracks; and on the basis of the P dynamic intermittent constraints, the movable atomization equipment is started to spray the formaldehyde scavenger in the target indoor space along the P spraying tracks. The technical problem of low formaldehyde treatment efficiency in the prior art is solved, and the technical effect of improving the formaldehyde treatment efficiency is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of formaldehyde treatment, and specifically to a formaldehyde treatment method and system for indoor environments. Background Art

[0002] As a common indoor air pollutant, formaldehyde widely exists in homes, office spaces, and building materials. Long-term exposure to formaldehyde can be harmful to human health. Therefore, how to effectively remove formaldehyde from indoor environments has become a research focus in the field of air purification. Existing formaldehyde removal methods mostly rely on air purifiers, chemical adsorbents, or sprays, etc. However, these methods generally have problems such as incomplete formaldehyde removal, uneven treatment effects, and slow treatment speeds. In addition, traditional formaldehyde treatment equipment is difficult to precisely control the spraying area and concentration of the scavenger, often resulting in unsatisfactory treatment effects in some areas. Especially in large indoor spaces, the distribution of formaldehyde is often uneven, and the existing technologies cannot effectively address this challenge. Summary of the Invention

[0003] This application provides a formaldehyde treatment method and system for indoor environments, which solves the technical problem of low formaldehyde treatment efficiency in the prior art.

[0004] In the first aspect of this application, a formaldehyde treatment method for indoor environments is provided. The method includes:

[0005] After obtaining calibrated ambient formaldehyde data by performing formaldehyde concentration drift compensation on the perception data of the target indoor space, generating a formaldehyde grid space by performing three-dimensional discrete mapping on the calibrated ambient formaldehyde data, where the formaldehyde grid has a virtual concentration release identifier; performing release body traceability in the formaldehyde grid space to obtain K formaldehyde release bodies, where the K formaldehyde release bodies are bound with K release characteristics and K groups of release-related grids; performing spraying task aggregation according to the distance-concentration characteristics of the K groups of release-related grids and the K formaldehyde release bodies to obtain P groups of grid spraying tasks; performing obstacle avoidance compensation on the P groups of grid spraying tasks to obtain P spraying trajectories, where the P spraying trajectories are bound with P dynamic intermittent constraints; starting a mobile atomization device along the P spraying trajectories based on the P dynamic intermittent constraints to spray a formaldehyde scavenger in the target indoor space.

[0006] In the second aspect of this application, a formaldehyde treatment system for indoor environments is provided. The system includes:

[0007] A data processing module is used to generate a formaldehyde grid space by performing three-dimensional discrete mapping on the calibrated ambient formaldehyde data after compensating for the formaldehyde concentration drift of the perception data of the target indoor space. Among them, the formaldehyde grid has a virtual release concentration identifier; a traceability module is used to perform release ontology traceability in the formaldehyde grid space to obtain K formaldehyde release ontologies, where the K formaldehyde release ontologies are bound with K release characteristics and K groups of release-related grids; an aggregation module is used to perform spraying task aggregation based on the distance-concentration characteristics of the K groups of release-related grids and the K formaldehyde release ontologies to obtain P groups of grid spraying tasks; a compensation module is used to perform obstacle avoidance compensation on the P groups of grid spraying tasks to obtain P spraying trajectories, and the P spraying trajectories are bound with P dynamic intermittent constraints; a control module is used to start a mobile atomization device along the P spraying trajectories based on the P dynamic intermittent constraints to spray formaldehyde scavenger in the target indoor space.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] After compensating for the formaldehyde concentration drift of the perception data of the target indoor space to obtain calibrated ambient formaldehyde data, a formaldehyde grid space is generated by performing three-dimensional discrete mapping on the calibrated ambient formaldehyde data. Among them, the formaldehyde grid has a virtual release concentration identifier. Release ontology traceability is performed in the formaldehyde grid space to obtain K formaldehyde release ontologies, where the K formaldehyde release ontologies are bound with K release characteristics and K groups of release-related grids. Then, spraying task aggregation is performed based on the distance-concentration characteristics of the K groups of release-related grids and the K formaldehyde release ontologies to obtain P groups of grid spraying tasks. Then, obstacle avoidance compensation is performed on the P groups of grid spraying tasks to obtain P spraying trajectories, and the P spraying trajectories are bound with P dynamic intermittent constraints. Based on the P dynamic intermittent constraints, a mobile atomization device is started along the P spraying trajectories to spray formaldehyde scavenger in the target indoor space. This solves the technical problem of low formaldehyde treatment efficiency in the prior art and achieves the technical effect of effectively improving the spraying effect of formaldehyde scavenger, enhancing the indoor formaldehyde treatment efficiency and uniformity, and ensuring better control of the air quality of the indoor environment through three-dimensional grid space modeling and spraying trajectory optimization. Description of the Drawings

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0011] Figure 1Schematic flow chart of the formaldehyde treatment method for indoor environment provided by the embodiments of the present application;

[0012] Figure 2 Schematic structural diagram of the formaldehyde treatment system for indoor environment provided by the embodiments of the present application.

[0013] Explanation of reference numerals: data processing module 11, traceability module 12, aggregation module 13, compensation module 14, control module 15. Detailed implementation manners

[0014] By providing a formaldehyde treatment method and system for indoor environment, the present application solves the technical problem of low formaldehyde treatment efficiency in the prior art.

[0015] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0016] It should be noted that the terms "include" and "have" are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server including a series of steps or units does not necessarily have to be limited to those clearly listed steps or units, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0017] Embodiment 1, as Figure 1 shown, the present application provides a formaldehyde treatment method for indoor environment, wherein the method includes:

[0018] After performing formaldehyde concentration drift compensation on the perception data of the target indoor space to obtain calibrated ambient formaldehyde data, a formaldehyde grid space is generated by performing three-dimensional discrete mapping on the calibrated ambient formaldehyde data, wherein the formaldehyde grid has a released virtual concentration identifier.

[0019] Perception devices (such as sensor networks) in the indoor environment collect formaldehyde concentration data, which is usually affected by environmental factors (such as temperature, humidity, etc.), resulting in data drift. The collected formaldehyde concentration data is corrected according to historical monitoring data and real-time environmental variables (such as temperature and humidity) to obtain calibrated ambient formaldehyde data.

[0020] Based on the calibrated formaldehyde concentration data, the system will perform a three-dimensional discrete mapping to generate a formaldehyde grid space. That is, the indoor space is discretized according to a preset grid scale. The indoor space will be divided into several small grid units, and the calibrated formaldehyde concentration data will be filled into each grid unit. The formaldehyde concentration value in each grid unit will be used as the concentration identifier for that unit, reflecting the formaldehyde concentration distribution in that area.

[0021] Furthermore, after obtaining the calibrated ambient formaldehyde data by compensating for the formaldehyde concentration drift in the perception data of the target indoor space, generating a formaldehyde grid space through three-dimensional discrete mapping of the calibrated ambient formaldehyde data includes:

[0022] Receiving the indoor environment ternary data transmitted back by the sensor network pre-deployed in the target indoor space; compensating for the formaldehyde concentration drift in the indoor environment ternary data and outputting the calibrated ambient formaldehyde data; discretizing the target indoor space using a preset grid scale to obtain an indoor grid space; and filling the calibrated ambient formaldehyde data into the indoor grid space using a concentration difference algorithm to obtain a formaldehyde grid space.

[0023] The system receives the indoor environment ternary data transmitted back by the sensor network pre-deployed in the target indoor space. The indoor environment ternary data includes temperature, humidity, and formaldehyde concentration. The received indoor environment ternary data may be affected by environmental factors such as temperature and humidity, resulting in drift in the formaldehyde concentration data. Therefore, the system compensates for the drift in the indoor environment ternary data; by using a preset drift compensation function, this process corrects the formaldehyde concentration data according to known environmental conditions (such as temperature and humidity changes) to obtain more accurate calibrated ambient formaldehyde data. After obtaining the calibrated ambient formaldehyde data, the system discretizes the target indoor space using a preset grid scale, that is, divides the target indoor space into several uniform small units to form an indoor grid space. Finally, the system uses a concentration difference algorithm to fill the obtained calibrated ambient formaldehyde data into the indoor grid space. Specifically, by performing interpolation calculations on the formaldehyde concentration in each grid unit, it is ensured that the concentration value of each grid unit can accurately reflect the formaldehyde concentration at that position in the target indoor space. After this processing, the obtained formaldehyde grid space contains the formaldehyde concentration information of each grid unit, forming a complete spatial mapping.

[0024] Furthermore, receiving the indoor environment ternary data transmitted back by the sensor network pre-deployed in the target indoor space includes:

[0025] According to the capabilities of the sensing devices and the distribution of entity configurations, locate the fusion sensing blind area and N reference sensing nodes in the target indoor space; perform mobile sensing deployment based on the fusion sensing blind area to obtain a mobile sensing trajectory; deploy N triple sensing units at the N reference sensing nodes; drive a mobile sensing device along the mobile sensing trajectory to collect blind area triple data of the fusion sensing blind area, and use the N triple sensing units to collect fixed-point triple data, where the mobile sensing device and the N triple sensing units constitute the sensor network; spatially align the blind area triple data and the fixed-point triple data as the indoor environment triple data to be transmitted back.

[0026] Preferably, according to the capabilities of the sensing devices and the distribution of entity configurations in the target indoor space, the system locates the fusion sensing blind area and N reference sensing nodes in the target indoor space. The fusion sensing blind area refers to the area that has not been covered or sensed under the existing sensor layout; the reference sensing nodes refer to the standard positions used to determine the sensor layout and sensing coverage in space. Based on the fusion sensing blind area, mobile sensing deployment is performed to obtain a mobile sensing trajectory. Specifically, identify the fusion sensing blind area in the indoor space that is not effectively covered due to the existing sensor arrangement; according to the capabilities of the sensing devices and the actual configuration of the indoor space, plan a mobile sensing trajectory to maximize the coverage of the fusion sensing blind area and ensure accurate collection of environmental data during movement.

[0027] At the N reference sensing nodes, the system deploys N triple sensing units, each of which can measure data such as temperature, humidity, and formaldehyde concentration simultaneously. The system collects blind area triple data along the mobile sensing trajectory through the mobile sensing device. At the same time, the N triple sensing units continue to collect fixed-point triple data, covering specific positions in space. The mobile sensing device and the triple sensing units together constitute the sensor network for the entire indoor environment, working together to provide comprehensive and accurate environmental data. The system spatially aligns the collected blind area triple data and fixed-point triple data to ensure their accuracy in the same coordinate system; the aligned data will be used as the indoor environment triple data to be transmitted back.

[0028] Furthermore, locating the fusion sensing blind area and N reference sensing nodes in the target indoor space according to the capabilities of the sensing devices and the distribution of entity configurations includes:

[0029] After setting the deployment density according to the capabilities of the sensing devices, M reference sensing nodes are equidistantly located in the target indoor space based on the deployment density; the entity configuration distribution of the target indoor space is called, and N reference sensing nodes are screened and determined from the M reference sensing nodes according to the entity configuration distribution; with the target indoor space as the sensing range constraint, the fusion sensing blind areas of the N reference sensing nodes are fitted and output.

[0030] The system sets the deployment density according to the capabilities and requirements of the sensing devices. The deployment density refers to the distribution density of the sensing devices in the target indoor space, which affects the accuracy and coverage of space perception. According to the set deployment density, the system equidistantly locates M reference sensing nodes in the target indoor space. Each reference sensing node represents a fixed sensing position, ensuring that the sensing devices deployed at these nodes can accurately monitor the indoor environment.

[0031] The system calls the entity configuration distribution information of the target indoor space. The entity configuration distribution refers to the distribution of actual objects or structures (such as walls, furniture, equipment, etc.) in the indoor space. Based on the entity configuration distribution, the system screens N reference sensing nodes from the already located M reference sensing nodes. Finally, with the target indoor space as the sensing range constraint, the system fits and outputs the fusion sensing blind areas; by analyzing the distribution and sensing range of the N reference sensing nodes, the system identifies the positions and ranges of these blind areas, and then conducts optimized deployment.

[0032] Furthermore, performing formaldehyde concentration drift compensation on the ternary data of the indoor environment and outputting the calibrated environmental formaldehyde data includes:

[0033] Locally calling the historical monitoring data of the target indoor space, where the historical monitoring data includes multiple sample temperature characteristics, multiple sample humidity characteristics, multiple sample standard formaldehyde concentrations, and multiple sample measured formaldehyde concentrations; retrieving network disturbance data by combining the multiple sample temperature characteristics and multiple sample humidity characteristics to expand the historical monitoring data and obtain disturbance monitoring data; constructing a drift compensation function based on the disturbance monitoring data; using the drift compensation function to perform formaldehyde concentration drift compensation on the ternary data of the indoor environment and outputting the calibrated environmental formaldehyde data.

[0034] The system locally calls the historical monitoring data of the target indoor space. The historical monitoring data includes multiple sample temperature characteristics, multiple sample humidity characteristics, multiple sample standard formaldehyde concentrations, and multiple sample measured formaldehyde concentrations. The historical monitoring data provides information on the change of formaldehyde concentration under different times and environmental conditions, and these data will be used as the basis for drift compensation to help the system identify and compensate for the drift phenomenon of formaldehyde concentration.

[0035] The system retrieves network disturbance data by combining multiple sample temperature features and multiple sample humidity features, that is, it expands the existing historical monitoring data according to the influence of temperature and humidity changes on formaldehyde concentration. By integrating more environmental variables, the system can more accurately evaluate the interference of environmental changes on formaldehyde concentration and obtain more comprehensive disturbance monitoring data.

[0036] Based on the obtained disturbance monitoring data, the system constructs a drift compensation function. Specifically, the system analyzes multiple variables in the disturbance monitoring data (such as changes in temperature, humidity, and formaldehyde concentration, etc.), identifies the mutual relationships between these variables, and then derives a mathematical model to describe the drift relationship between formaldehyde concentration and environmental factors (such as temperature, humidity, etc.). Optionally, preprocess the disturbance monitoring data, remove noise data and standardize samples under different time periods and environmental conditions to ensure the consistency and accuracy of the data; then, analyze the correlation between formaldehyde concentration and other environmental factors (such as temperature, humidity, etc.). Through statistical analysis methods (such as regression analysis, covariance analysis, etc.), the system identifies how these factors act together to affect the change of formaldehyde concentration; according to the results of the correlation analysis, the system constructs a drift compensation function that can correct the formaldehyde concentration according to the changes of variables such as temperature and humidity under different environmental conditions.

[0037] The system uses the constructed drift compensation function to perform drift compensation on the formaldehyde concentration in the indoor environment ternary data. Through drift compensation, the system can output the calibrated formaldehyde concentration data as more accurate calibrated environmental formaldehyde data, thus providing more accurate data support for subsequent formaldehyde removal tasks.

[0038] Release body tracing is carried out in the formaldehyde grid space to obtain K formaldehyde release bodies, where the K formaldehyde release bodies are bound with K release features and K groups of release-related grid networks.

[0039] The system conducts release body tracing in the formaldehyde grid space. The release body refers to the source or origin of formaldehyde release in the indoor environment, such as the actual location, size, and release characteristics of formaldehyde pollution sources, etc. By analyzing the spatial gradient, distribution pattern, and change trend of formaldehyde concentration, the system can trace and determine the location and characteristics of these formaldehyde release sources. According to the distribution and change of formaldehyde concentration, the system finally identifies K formaldehyde release bodies, which represent the source areas of formaldehyde pollution and are usually related to indoor furniture, building materials, equipment, etc.

[0040] After identifying K formaldehyde-releasing entities, the system will bind K release characteristics to each releasing entity. These characteristics include formaldehyde release rate, release pattern, duration, etc. Correspondingly, the system will also bind K sets of release-related grids to each releasing entity. The release-related grids are associated with the spatial distribution and changes of formaldehyde concentration. Through the release-related grids, the system can accurately describe the relationship between each releasing entity and the surrounding environment, as well as their impact on the overall indoor formaldehyde concentration distribution.

[0041] Furthermore, in the formaldehyde grid space, source tracing of the releasing entities is performed to obtain K formaldehyde-releasing entities, including:

[0042] By calculating the concentration gradient vector of the formaldehyde grid space, a gradient vector matrix is obtained; a low-concentration quantization threshold and a high-concentration quantization threshold are preset, and the release virtual concentration of the formaldehyde grid space is traversed using the low-concentration quantization threshold and the high-concentration quantization threshold to locate R low-concentration grids and U high-concentration grids; starting from the R low-concentration grids and U high-concentration grids, two-way tracking of the concentration change is performed along the gradient vector matrix to locate the K formaldehyde-releasing entities.

[0043] The system calculates the concentration gradient vector based on the concentration data in the formaldehyde grid space. The concentration gradient vector represents the change direction and change rate of formaldehyde concentration in space. The concentration gradient refers to the direction and rate of change of formaldehyde concentration in the formaldehyde grid space. Optionally, the difference method (such as the finite difference method) is used to calculate the concentration gradient. According to the concentration values of each grid cell, the concentration differences between adjacent grid cells are calculated, and the direction and magnitude of the concentration gradient are calculated using these differences; where, is the concentration gradient vector, respectively represent the change rates of concentration in each direction (x, y, z axes). By calculating the concentration gradient of each grid cell, the system generates a gradient vector matrix that contains the concentration gradient information of each grid cell in the entire formaldehyde grid space.

[0044] The system presets low-concentration quantization thresholds and high-concentration quantization thresholds to define the low-concentration and high-concentration regions of formaldehyde concentration. By traversing the virtual release concentrations in the formaldehyde grid space, the system uses these thresholds to divide the space into low-concentration regions and high-concentration regions. Specifically, the system locates R low-concentration grids and U high-concentration grids according to the set thresholds, and these grids correspond to the regions with low and high formaldehyde concentrations respectively. Starting from the located R low-concentration grids and U high-concentration grids, the system performs two-way tracking of concentration changes along the gradient vector matrix. The two-way tracking process involves tracking the increasing path of concentration from low-concentration grids to high-concentration grids, and also tracking the decreasing path of concentration from high-concentration grids to low-concentration grids. The two-way tracking method can accurately identify the source of formaldehyde concentration changes and locate K formaldehyde release entities, that is, the positions of formaldehyde release sources.

[0045] Furthermore, starting from the R low-concentration grids and U high-concentration grids, performing two-way tracking of concentration changes along the gradient vector matrix, and locating the K formaldehyde release entities includes:

[0046] Starting from the R low-concentration grids, using forward streamline integration to track concentration changes along the gradient vector matrix to locate the distribution of formaldehyde release sources; expanding the U high-concentration grids to Q high-concentration grids in the formaldehyde grid space according to the distribution of formaldehyde release sources; starting from the Q high-concentration grids, performing source point consistency verification on the R low-concentration grids along the gradient vector matrix; if the source point consistency verification result is set to 1, then call the entity configuration distribution of the target indoor space, and obtain the K formaldehyde release entities by projecting the Q high-concentration grids onto the entity configuration distribution.

[0047] The system takes the R low-concentration grids as starting points respectively, uses the forward streamline integration method, and tracks concentration changes along the gradient vector matrix until the position of the formaldehyde release source is located; specifically, the forward streamline integration calculates the path starting from the low-concentration grids, along the direction of the gradient vector matrix, and gradually tracks concentration changes along each grid cell; at each step, the next position is determined according to the gradient information and the tracking continues until reaching the high-concentration region or stopping according to preset conditions.

[0048] When tracking concentration changes, the system tracks the change path of formaldehyde concentration from low-concentration grids to high-concentration grids according to the gradient of formaldehyde concentration in the space. The concentration value of each grid cell is updated as the tracking progresses to reflect the diffusion of formaldehyde concentration in the space. Through the forward streamline integration method, the system can track the main path of formaldehyde concentration changes, thereby determining the position of the formaldehyde release source.

[0049] Based on the obtained formaldehyde emission source distribution, the system will expand U high-concentration grids to Q high-concentration grids in the formaldehyde grid space, that is, by analyzing the distribution of formaldehyde concentration, identify other areas where relatively high-concentration formaldehyde may exist, and include these areas as new high-concentration grids for consideration. Next, starting from the Q high-concentration grids, the system performs source point consistency verification on the R low-concentration grids along the gradient vector matrix to confirm whether the positioning of the formaldehyde emission source is consistent and to determine whether the concentration change between the low-concentration grids and the high-concentration grids conforms to the characteristics of the formaldehyde emission source. If the result of the consistency verification is 1, indicating that the source point verification passes, the system can confirm the location and characteristics of the formaldehyde emission source. If the source point consistency verification passes, the system will call the entity configuration distribution information of the target indoor space and perform matching by projecting the Q high-concentration grids onto the entity configuration distribution. Through this matching, the system can finally obtain the accurate locations and characteristics of K formaldehyde emission entities.

[0050] According to the distance-concentration characteristics of the K groups of release-related grids and the K formaldehyde emission entities, spray task aggregation is performed to obtain P groups of grid spray tasks.

[0051] The system analyzes the formaldehyde concentration distribution of each grid unit in the K groups of release-related grids and its association with the formaldehyde emission entity according to the distance-concentration characteristics. Grids closer in distance usually have higher concentration values, while grids far from the emission entity have lower concentrations; the system uses this information to determine which areas require more spray tasks and reasonably allocate the spray volume.

[0052] After obtaining the concentration characteristics and distance information of each grid unit, the system will perform spray task aggregation based on these data, that is, considering the priority spray tasks for areas with relatively high formaldehyde concentration, and merge multiple related grids into one spray task. After task aggregation, the system will obtain P groups of grid spray tasks, and each group of spray tasks represents an optimized spray area, including the appropriate spray volume, spray mode, and selection of the spray area. The P groups of grid spray tasks cover all areas of the indoor space and Q emission sources, ensuring the effective removal of formaldehyde pollution in the indoor space.

[0053] Furthermore, according to the distance-concentration characteristics of the K groups of release-related grids and the K formaldehyde emission entities, spray task aggregation is performed to obtain P groups of grid spray tasks, including:

[0054] Based on the distance-concentration characteristic deviations between the K sets of release-related grids and the K formaldehyde release bodies, calculate and output K sets of initial spraying cycles; preset a cycle deviation scale and a concentration deviation scale; use the cycle deviation scale and the concentration deviation scale as double aggregation constraints, traverse the K sets of release virtual concentrations and the K sets of initial spraying cycles, and perform grid-level spraying task aggregation on the formaldehyde grid space to obtain P sets of grid spraying tasks.

[0055] The distance-concentration characteristic deviation reflects the concentration difference and its spatial distance between each grid and the formaldehyde release body; the system calculates the initial spraying cycle based on the distance-concentration characteristic deviation of each formaldehyde release body. The spraying cycle refers to the spraying interval time in the formaldehyde removal task, which directly affects the efficiency and removal effect of the spraying operation. The system uses the deviations of distance and concentration as input variables and uses a preset calculation model (such as weighted average, regression analysis, or other statistical models) to calculate an initial spraying cycle for each grid cell. Generally, areas with a shorter distance and higher concentration will have a shorter spraying cycle to ensure the timeliness of formaldehyde removal; while areas with a longer distance and lower concentration may have a longer spraying cycle. Based on the above calculation results, the system outputs K sets of initial spraying cycles, with each set corresponding to the spraying task cycle of a formaldehyde release body and its related grid cells.

[0056] The system presets a cycle deviation scale and a concentration deviation scale. The cycle deviation scale is mainly used to adjust the differences between spraying cycles, while the concentration deviation scale is used to adjust the error range of concentration changes. The system uses the cycle deviation scale and the concentration deviation scale as double aggregation constraints and performs grid-level spraying task aggregation on the formaldehyde grid space when traversing the K sets of release virtual concentrations and the K sets of initial spraying cycles.

[0057] The system traverses according to the K sets of release virtual concentrations (representing the formaldehyde concentration of each grid cell) and the K sets of initial spraying cycles (representing the time intervals for formaldehyde removal). During the traversal process, the system checks the concentration level and the initial spraying cycle of each grid cell one by one and adjusts them in combination with the cycle deviation scale and the concentration deviation scale. During the traversal process, the system will perform grid-level spraying task aggregation on each grid cell in the formaldehyde grid space. Through the action of the double aggregation constraints, the system will merge the spraying tasks of adjacent grid cells into an overall task, reduce redundant spraying, and optimize the spraying path and cycle arrangement. By performing grid-level spraying task aggregation on the formaldehyde grid space, P sets of grid spraying tasks are obtained.

[0058] Perform obstacle avoidance compensation on the P sets of grid spraying tasks to obtain P spraying trajectories, and the P spraying trajectories are bound with P dynamic intermittent constraints.

[0059] The system performs obstacle avoidance compensation on the P-group grid spraying tasks, generates P spraying trajectories, and binds P dynamic intermittent constraints to each trajectory. Specifically, the system adjusts the path of the spraying tasks through obstacle avoidance compensation to ensure that the spraying equipment can bypass indoor obstacles and smoothly execute the spraying tasks; based on the optimized path, it generates the spraying trajectories for each spraying task, and each trajectory is bound with dynamic intermittent constraints that define the interval time or pause time required during the movement of the spraying equipment to ensure that the spraying agent is evenly distributed to each area and optimize the spraying efficiency; through these optimized trajectories and constraints, it guides the spraying equipment to efficiently and precisely execute the formaldehyde removal tasks.

[0060] Furthermore, obstacle avoidance compensation is performed on the P-group grid spraying tasks to obtain P spraying trajectories, and the P spraying trajectories are bound with P dynamic intermittent constraints, including:

[0061] Reorganize the K-group initial spraying cycles according to the P-group grid spraying tasks to obtain P-group grid spraying cycles; arrange the P-group grid spraying tasks in ascending order according to the P-group grid spraying cycles to obtain P spraying task sequences; perform obstacle avoidance trajectory fitting on the P spraying task sequences according to the entity configuration distribution to obtain the P spraying trajectories; calculate the time consumption of the P spraying trajectories, and determine the P dynamic intermittent constraints according to the calculation results and the P-group grid spraying cycles.

[0062] The system reorganizes the K-group initial spraying cycles according to the P-group grid spraying tasks. Each grid spraying task has an initial spraying cycle, and the system adjusts the initial spraying cycle according to the characteristics of each task (such as formaldehyde concentration, spraying area size, etc.) to generate P-group grid spraying cycles. Then, the system arranges the spraying tasks in ascending order according to the P-group grid spraying cycles, sorting the tasks according to the length of the spraying cycle. After the ascending arrangement, the system obtains P spraying task sequences, and these sequences are arranged according to the priority of the spraying cycles to ensure that high-concentration areas are sprayed first and the spraying operations are carried out in the most optimized time sequence.

[0063] After the spraying task sequences are determined, the system performs obstacle avoidance trajectory fitting on the P spraying task sequences according to the entity configuration distribution in the indoor space, obtaining P spraying task sequences. Specifically, the system acquires the entity configuration distribution information of the target indoor space, including the specific positions and shapes of all obstacles (such as walls, furniture, equipment, etc.) in the indoor space; based on the P spraying task sequences, the system takes information such as the starting point, target point, spraying area, and spraying cycle of each spraying task as input for path planning; during the path planning process, the system combines the entity configuration distribution information and uses an obstacle avoidance algorithm to calculate the optimal trajectory for each spraying task, ensuring that the spraying equipment can bypass indoor obstacles and avoid collisions with any objects; finally, the system generates a spraying trajectory for each spraying task, obtaining P spraying trajectories, which will guide the spraying equipment to move along the predetermined path to complete the formaldehyde removal task, ensuring accurate and obstacle-free coverage of each area to be sprayed.

[0064] The system calculates the time consumption of the P spraying trajectories according to the characteristics of each spraying task and the actual operating parameters of the equipment, estimates the execution time of each spraying task, and determines P dynamic intermittent constraints based on the calculation results and the P sets of grid spraying cycles. The dynamic intermittent constraints specify the interval time or pause time between each spraying task to ensure that the operation rhythm of the equipment during the spraying task is both efficient and does not cause excessive energy consumption or uneven spraying.

[0065] Based on the P dynamic intermittent constraints, start the mobile atomizing device along the P spraying trajectories to spray formaldehyde scavenger in the target indoor space.

[0066] After completing the planning of the spraying trajectories and determining the dynamic intermittent constraints, the system starts the mobile atomizing device and instructs it to work according to the generated P spraying trajectories. The mobile atomizing device usually includes an atomizing nozzle and a driving device, and can move autonomously in the indoor space and precisely control the spraying path. The mobile atomizing device moves along the predetermined P spraying trajectories and sprays formaldehyde scavenger at each trajectory point as planned; when the device is performing the task, it will make appropriate pauses and adjustments according to these dynamic intermittent constraints to ensure the precise spraying and efficient coverage of the formaldehyde scavenger.

[0067] In summary, the embodiments of the present application have at least the following technical effects:

[0068] After compensating for the formaldehyde concentration drift of the perception data of the target indoor space to obtain calibrated ambient formaldehyde data, a formaldehyde grid space is generated by performing three-dimensional discrete mapping on the calibrated ambient formaldehyde data. Among them, the formaldehyde grid has a virtual release concentration identifier. Release ontology tracing is performed in the formaldehyde grid space to obtain K formaldehyde release ontologies, where the K formaldehyde release ontologies are bound with K release characteristics and K groups of release-related grids. Then, according to the distance-concentration characteristics of the K groups of release-related grids and the K formaldehyde release ontologies, spraying task aggregation is performed to obtain P groups of grid spraying tasks. Then, obstacle avoidance compensation is performed on the P groups of grid spraying tasks to obtain P spraying trajectories, and the P spraying trajectories are bound with P dynamic intermittent constraints. Based on the P dynamic intermittent constraints, a mobile atomization device is started to spray formaldehyde scavenger in the target indoor space along the P spraying trajectories. It solves the technical problem of low formaldehyde treatment efficiency in the prior art, and achieves the technical effect of effectively improving the spraying effect of the formaldehyde scavenger, enhancing the indoor formaldehyde treatment efficiency and uniformity, and ensuring better control of the air quality of the indoor environment through three-dimensional grid space modeling and spraying trajectory optimization.

[0069] Embodiment 2, based on the same inventive concept as the formaldehyde treatment method for indoor environment in the foregoing embodiment, as Figure 2 shown, the present application provides a formaldehyde treatment system for indoor environment, wherein the system includes:

[0070] A data processing module 11, configured to, after compensating for the formaldehyde concentration drift of the perception data of the target indoor space to obtain calibrated ambient formaldehyde data, generate a formaldehyde grid space by performing three-dimensional discrete mapping on the calibrated ambient formaldehyde data, wherein the formaldehyde grid has a virtual release concentration identifier; a tracing module 12, configured to perform release ontology tracing in the formaldehyde grid space to obtain K formaldehyde release ontologies, where the K formaldehyde release ontologies are bound with K release characteristics and K groups of release-related grids; an aggregation module 13, configured to perform spraying task aggregation according to the distance-concentration characteristics of the K groups of release-related grids and the K formaldehyde release ontologies to obtain P groups of grid spraying tasks; a compensation module 14, configured to perform obstacle avoidance compensation on the P groups of grid spraying tasks to obtain P spraying trajectories, and the P spraying trajectories are bound with P dynamic intermittent constraints; a control module 15, configured to start a mobile atomization device to spray formaldehyde scavenger in the target indoor space along the P spraying trajectories based on the P dynamic intermittent constraints.

[0071] Further, the tracing module 12 is configured to execute the following method:

[0072] By calculating the concentration gradient vector of the formaldehyde grid space, a gradient vector matrix is obtained; a low-concentration quantization threshold and a high-concentration quantization threshold are preset, and the virtual release concentration of the formaldehyde grid space is traversed using the low-concentration quantization threshold and the high-concentration quantization threshold to locate R low-concentration grids and U high-concentration grids; starting from the R low-concentration grids and U high-concentration grids, two-way tracking of concentration changes is performed along the gradient vector matrix to locate the K formaldehyde release bodies.

[0073] Further, the traceability module 12 is used to execute the following method:

[0074] Starting from the R low-concentration grids, forward streamline integration is used to track concentration changes along the gradient vector matrix to locate the distribution of formaldehyde release sources; the U high-concentration grids are extended to Q high-concentration grids in the formaldehyde grid space according to the distribution of formaldehyde release sources; starting from the Q high-concentration grids, source point consistency verification is performed on the R low-concentration grids along the gradient vector matrix; if the source point consistency verification result is set to 1, the entity configuration distribution of the target indoor space is called, and the K formaldehyde release bodies are obtained by projecting the Q high-concentration grids onto the entity configuration distribution for matching.

[0075] Further, the aggregation module 13 is used to execute the following method:

[0076] According to the distance-concentration characteristic deviation between the K groups of release-related grids and the K formaldehyde release bodies, K groups of initial spraying periods are calculated and output; a period deviation scale and a concentration deviation scale are preset; the period deviation scale and the concentration deviation scale are used as double aggregation constraints to traverse the K groups of virtual release concentrations and the K groups of initial spraying periods, and grid-level spraying task aggregation is performed on the formaldehyde grid space to obtain P groups of grid spraying tasks.

[0077] Further, the data processing module 11 is used to execute the following method:

[0078] Receive the indoor environment three-element data transmitted back by the sensor network pre-deployed in the target indoor space; perform formaldehyde concentration drift compensation on the indoor environment three-element data and output the calibrated environmental formaldehyde data; discretize the target indoor space using a preset grid scale to obtain an indoor grid space; use a concentration difference algorithm to fill the calibrated environmental formaldehyde data into the indoor grid space to obtain a formaldehyde grid space.

[0079] Further, the data processing module 11 is used to execute the following method:

[0080] According to the capabilities of the sensing devices and the distribution of entity configurations, locate the fusion sensing blind spots and N reference sensing nodes in the target indoor space; perform mobile sensing deployment based on the fusion sensing blind spots to obtain a mobile sensing trajectory; deploy N triple sensing units at the N reference sensing nodes; drive a mobile sensing device along the mobile sensing trajectory to collect blind spot triple data of the fusion sensing blind spots, and use the N triple sensing units to collect fixed-point triple data, where the mobile sensing device and the N triple sensing units constitute the sensor network; spatially align the blind spot triple data and the fixed-point triple data as the indoor environment triple data to be transmitted back.

[0081] Further, the data processing module 11 is configured to execute the following method:

[0082] After setting the deployment density according to the capabilities of the sensing devices, locate M reference sensing nodes equidistantly in the target indoor space based on the deployment density; call the entity configuration distribution of the target indoor space, and screen and determine the N reference sensing nodes from the M reference sensing nodes according to the entity configuration distribution; with the target indoor space as the sensing range constraint, fit and output the fusion sensing blind spots of the N reference sensing nodes.

[0083] Further, the data processing module 11 is configured to execute the following method:

[0084] Locally call the historical monitoring data of the target indoor space, where the historical monitoring data includes multiple sample temperature features, multiple sample humidity features, multiple sample standard formaldehyde concentrations, and multiple sample measured formaldehyde concentrations; perform network perturbation data retrieval by combining the multiple sample temperature features and multiple sample humidity features to expand the historical monitoring data and obtain perturbed monitoring data; construct a drift compensation function based on the perturbed monitoring data; use the drift compensation function to perform formaldehyde concentration drift compensation on the indoor environment triple data and output the calibrated environmental formaldehyde data.

[0085] Further, the compensation module 14 is configured to execute the following method:

[0086] Recombine the K groups of initial spraying cycles according to the P groups of grid spraying tasks to obtain P groups of grid spraying cycles; arrange the P groups of grid spraying tasks in ascending order according to the P groups of grid spraying cycles to obtain P spraying task sequences; perform obstacle avoidance trajectory fitting on the P spraying task sequences according to the entity configuration distribution to obtain the P spraying trajectories; calculate the time consumption of the P spraying trajectories, and determine the P dynamic intermittent constraints according to the calculation results and the P groups of grid spraying cycles.

[0087] It should be noted that the above sequence of embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above description of specific embodiments of this specification has been made. The processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0088] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

[0089] This specification and the drawings are only exemplary descriptions of the present application and are considered to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A formaldehyde treatment method for indoor environment, characterized in that, The method includes: After compensating for the formaldehyde concentration drift of the perception data of the target indoor space to obtain calibrated ambient formaldehyde data, a formaldehyde grid space is generated by performing three-dimensional discrete mapping on the calibrated ambient formaldehyde data, where the formaldehyde grid has a virtual release concentration identifier; Performing release ontology tracing in the formaldehyde grid space to obtain K formaldehyde release ontologies, where the K formaldehyde release ontologies are bound with K release characteristics and K groups of release-related grids; Performing spraying task aggregation according to the distance-concentration characteristics of the K groups of release-related grids and the K formaldehyde release ontologies to obtain P groups of grid spraying tasks; Performing obstacle avoidance compensation on the P groups of grid spraying tasks to obtain P spraying trajectories, where the P spraying trajectories are bound with P dynamic intermittent constraints; Based on the P dynamic intermittent constraints, starting a mobile atomizing device to spray formaldehyde scavenger in the target indoor space along the P spraying trajectories.

2. The formaldehyde treatment method for indoor environment according to claim 1, wherein, Performing release ontology tracing in the formaldehyde grid space to obtain K formaldehyde release ontologies, the method includes: Calculating the concentration gradient vector of the formaldehyde grid space to obtain a gradient vector matrix; Presetting a low-concentration quantization threshold and a high-concentration quantization threshold, and traversing the virtual release concentration of the formaldehyde grid space using the low-concentration quantization threshold and the high-concentration quantization threshold to locate R low-concentration grids and U high-concentration grids; Starting from the R low-concentration grids and the U high-concentration grids, performing two-way tracking of the concentration change along the gradient vector matrix to locate the K formaldehyde release ontologies.

3. The formaldehyde treatment method for indoor environment according to claim 2, characterized in that, Starting from the R low-concentration grids and the U high-concentration grids, performing two-way tracking of the concentration change along the gradient vector matrix to locate the K formaldehyde release ontologies, the method includes: Starting from the R low-concentration grids, using forward streamline integration to perform concentration change tracking along the gradient vector matrix to locate the formaldehyde release source distribution; Expanding the U high-concentration grids to Q high-concentration grids in the formaldehyde grid space according to the formaldehyde release source distribution; Starting from the Q high-concentration grids, performing source point consistency verification on the R low-concentration grids along the gradient vector matrix; If the source point consistency verification result is set to 1, then call the entity configuration distribution of the target indoor space, and match the Q high-concentration grids to the entity configuration distribution to obtain the K formaldehyde release ontologies.

4. The formaldehyde treatment method for indoor environment according to claim 3, characterized in that, Performing spraying task aggregation according to the distance-concentration characteristics of the K groups of release-related grids and the K formaldehyde release ontologies to obtain P groups of grid spraying tasks, the method includes: Calculating and outputting K groups of initial spraying periods according to the distance-concentration characteristic deviations of the K groups of release-related grids and the K formaldehyde release ontologies; Presetting a period deviation scale and a concentration deviation scale; Using the period deviation scale and the concentration deviation scale as double aggregation constraints, traversing the K groups of release virtual concentrations and the K groups of initial spraying periods, and performing grid-level spraying task aggregation on the formaldehyde grid space to obtain P groups of grid spraying tasks.

5. The formaldehyde treatment method for indoor environment according to claim 1, characterized in that, After obtaining calibrated ambient formaldehyde data by compensating for formaldehyde concentration drift in the perception data of the target indoor space, a formaldehyde grid space is generated by performing three-dimensional discrete mapping on the calibrated ambient formaldehyde data. The method includes: Receiving indoor environmental ternary data transmitted back by a sensor network pre-deployed in the target indoor space; Compensating for formaldehyde concentration drift in the indoor environmental ternary data and outputting the calibrated ambient formaldehyde data; Discretizing the target indoor space using a preset grid scale to obtain an indoor grid space; Using a concentration difference algorithm to fill the calibrated ambient formaldehyde data into the indoor grid space to obtain a formaldehyde grid space.

6. The formaldehyde treatment method for indoor environment according to claim 5, wherein Receiving indoor environmental ternary data transmitted back by a sensor network pre-deployed in the target indoor space, the method includes: Locating a fusion perception blind area and N reference perception nodes in the target indoor space according to the perception device capabilities and entity configuration distribution; Performing mobile perception deployment according to the fusion perception blind area to obtain a mobile perception trajectory; Deploying N ternary perception units at the N reference perception nodes; Driving a mobile perception device to collect blind area ternary data in the fusion perception blind area according to the mobile perception trajectory, and using the N ternary perception units to collect fixed-point ternary data, where the mobile perception device and the N ternary perception units constitute the sensor network; Spatially aligning the blind area ternary data and the fixed-point ternary data as the transmitted-back indoor environmental ternary data.

7. The formaldehyde treatment method for indoor environment according to claim 6, wherein, Locating a fusion perception blind area and N reference perception nodes in the target indoor space according to the perception device capabilities and entity configuration distribution, the method includes: After setting the deployment density according to the perception device capabilities, locating M reference perception nodes equidistantly in the target indoor space based on the deployment density; Invoking the entity configuration distribution of the target indoor space and screening and determining the N reference perception nodes from the M reference perception nodes according to the entity configuration distribution; Taking the target indoor space as the perception range constraint and fitting and outputting the fusion perception blind area of the N reference perception nodes.

8. The formaldehyde treatment method for indoor environment according to claim 5, characterized in that, Compensating for formaldehyde concentration drift in the indoor environmental ternary data and outputting the calibrated ambient formaldehyde data, the method includes: Locally invoking the historical monitoring data of the target indoor space, where the historical monitoring data includes multiple sample temperature features, multiple sample humidity features, multiple sample standard formaldehyde concentrations, and multiple sample measured formaldehyde concentrations; Retrieving network perturbation data by combining the multiple sample temperature features and multiple sample humidity features to expand the historical monitoring data and obtain perturbed monitoring data; Constructing a drift compensation function based on the perturbed monitoring data; Using the drift compensation function to compensate for formaldehyde concentration drift in the indoor environmental ternary data and outputting the calibrated ambient formaldehyde data.

9. The formaldehyde treatment method for indoor environment according to claim 4, characterized in that, Performing obstacle avoidance compensation on the P groups of grid spraying tasks to obtain P spraying trajectories, and the P spraying trajectories are bound with P dynamic intermittent constraints. The method includes: Recombining the K groups of initial spraying cycles according to the P groups of grid spraying tasks to obtain P groups of grid spraying cycles; Arrange the P groups of grid spraying tasks in ascending order according to the P group grid spraying periods to obtain P spraying task sequences; Perform obstacle avoidance trajectory fitting on the P spraying task sequences according to the entity configuration distribution to obtain the P spraying trajectories; Calculate the time consumption of the P spraying trajectories, and determine the P dynamic intermittent constraints according to the calculation results and the P group grid spraying periods.

10. A formaldehyde treatment system for indoor environments, characterized in that, For implementing the formaldehyde treatment method for indoor environment according to any one of claims 1-9, the system includes: A data processing module, configured to generate a formaldehyde grid space by performing three-dimensional discrete mapping on the calibrated ambient formaldehyde data after compensating the formaldehyde concentration drift of the perception data of the target indoor space, wherein the formaldehyde grid has a released virtual concentration identifier; A tracing module, configured to perform release body tracing in the formaldehyde grid space to obtain K formaldehyde release bodies, wherein the K formaldehyde release bodies are bound with K release characteristics and K groups of release related grids; An aggregation module, configured to perform spraying task aggregation according to the distance-concentration characteristics between the K groups of release related grids and the K formaldehyde release bodies to obtain P groups of grid spraying tasks; A compensation module, configured to perform obstacle avoidance compensation on the P groups of grid spraying tasks to obtain P spraying trajectories, and the P spraying trajectories are bound with P dynamic intermittent constraints; A control module, configured to start a mobile atomizing device along the P spraying trajectories based on the P dynamic intermittent constraints to spray a formaldehyde scavenger in the target indoor space.

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