Formaldehyde removal method, device and equipment for building, storage medium and product

Abstract

The invention discloses a formaldehyde removal method and device for a building, equipment, a storage medium and a product, relates to the technical field of intelligent environmental protection, and discloses the formaldehyde removal method for the building, and the method comprises the steps: obtaining temperature distribution in a target area and a surface image of a target object under the condition of receiving a starting instruction; determining potential release source information of the binding-state formaldehyde based on the temperature distribution; based on the surface image, determining material information of the target object, and based on the material information, determining release trend information of the free-state formaldehyde; and generating a corresponding formaldehyde removal strategy based on the release source information and the release trend information, and executing the formaldehyde removal strategy to obtain a formaldehyde removal result. According to the method, the potential release source information of the binding-state formaldehyde is determined by acquiring the temperature distribution and the surface image in the target area, and the formaldehyde removal strategy is generated. The formaldehyde release source and the formaldehyde in the air can be treated at the same time, so that the effect of removing the formaldehyde in the building range is improved.

Description

Technical Field

[0001] This application relates to the field of intelligent environmental protection technology, and particularly to a formaldehyde removal method, device, equipment, storage medium and product for buildings. Background Art

[0002] With the improvement of people's living standards, the impact of indoor air quality on human health has been increasingly concerned. Formaldehyde is a common indoor air pollutant, mainly sourced from decoration materials, furniture, etc. Formaldehyde exists in the indoor environment in the forms of free state, adsorbed state and bound state. Free formaldehyde is directly released into the air and can be removed by ventilation, adsorption, etc.; bound formaldehyde is hidden inside the materials and gradually released with environmental changes, making it difficult to eradicate.

[0003] In related technologies, an air purifier with a formaldehyde decomposition function is usually used to remove formaldehyde within the building range and reduce the indoor formaldehyde concentration. However, this method can only treat pollutants in the air, that is, it can only remove free formaldehyde, and cannot directly act on the pollution source, resulting in a low effect of removing formaldehyde within the building range.

[0004] The above content is only used to assist in understanding the technical solution of this application, and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a formaldehyde removal method for buildings, aiming to solve the technical problem of the low effect of removing formaldehyde within the building range currently.

[0006] To achieve the above purpose, this application proposes a formaldehyde removal method for buildings, and the formaldehyde removal method for buildings includes:

[0007] When a start instruction is received, obtain the temperature distribution in the target area and the surface image of the target object;

[0008] Based on the temperature distribution, determine the potential release source information of bound formaldehyde;

[0009] Based on the surface image, determine the material information of the target object, and based on the material information, determine the release trend information of free formaldehyde;

[0010] Based on the release source information and the release trend information, generate a corresponding formaldehyde removal strategy, execute the formaldehyde removal strategy, and obtain a formaldehyde removal result.

[0011] Optionally, the step of based on the surface image, determine the material information of the target object, and based on the material information, determine the release trend information of free formaldehyde includes:

[0012] Extract the feature information of the target object from the surface image;

[0013] Based on the feature information, identify the material information of the target object;

[0014] Based on a preset mapping database, match the material information to obtain the release trend information of free formaldehyde, where the mapping database includes mapping information between multiple object materials and release trends.

[0015] Optionally, the step of determining the potential release source information of bound formaldehyde based on the temperature distribution includes:

[0016] Based on the temperature distribution, determine the temperature change information of each region in the target area, where the temperature change information includes the temperature rise value and the rise time;

[0017] Based on the temperature rise value and the rise time, determine the formaldehyde release stage;

[0018] Based on a preset formaldehyde release law database and the formaldehyde release stage, match the temperature change information to obtain the potential release source information of bound formaldehyde.

[0019] Optionally, the step of generating a corresponding formaldehyde removal strategy based on the release source information and the release trend information includes:

[0020] Based on the release source information and the release trend information, perform parameter prediction through a preset parameter adjustment model to obtain target parameters, where the target parameters include the heating temperature and the adsorption frequency, and the parameter adjustment model is obtained by iteratively training a preset model to be trained based on release source information samples, release trend information samples, and corresponding parameter result labels;

[0021] Based on the heating temperature and the adsorption frequency, form a formaldehyde removal strategy.

[0022] Optionally, before the step of performing parameter prediction through a preset parameter adjustment model based on the release source information and the release trend information to obtain target parameters, the method includes:

[0023] Obtain an information sample set, the environmental light intensity information corresponding to the information sample set, and the parameter result labels of the information sample set, where the information sample set includes release source information samples and release trend information samples;

[0024] Based on the environmental light intensity information, determine the environmental light weight;

[0025] Iteratively train a preset model to be trained based on the information sample set, the environmental light weight, and the parameter result label to obtain a parameter adjustment model.

[0026] Optionally, the step of iteratively training a preset model to be trained based on the information sample set, the environmental light weight, and the parameter result label to obtain a parameter adjustment model includes:

[0027] Input the information sample set and the environmental light weight into a preset model to be trained to obtain a predicted parameter result;

[0028] Calculate the difference between the predicted parameter result and the parameter result label to obtain an error result;

[0029] Based on the error result, determine whether the error result meets the error standard indicated by a preset error threshold range;

[0030] If the error result does not meet the error standard indicated by the preset error threshold range, return to the step of inputting the information sample set and the environmental light weight into a preset model to be trained to obtain a predicted parameter result, and stop training until the error result meets the error standard indicated by the preset error threshold range to obtain a parameter adjustment model that meets the accuracy condition.

[0031] In addition, to achieve the above object, the present application also proposes a formaldehyde removal device for a building, and the formaldehyde removal device for a building includes:

[0032] An acquisition module, configured to acquire the temperature distribution in a target area and the surface image of a target object when receiving a start instruction;

[0033] A release source information determination module, configured to determine the potential release source information of bound formaldehyde based on the temperature distribution;

[0034] A release trend determination module, configured to determine the material information of the target object based on the surface image, and determine the release trend information of free formaldehyde based on the material information;

[0035] A generation module, configured to generate a corresponding formaldehyde removal strategy based on the release source information and the release trend information, execute the formaldehyde removal strategy, and obtain a formaldehyde removal result.

[0036] In addition, to achieve the above object, the present application also proposes a formaldehyde removal device for a building, and the device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the formaldehyde removal method for a building as described above.

[0037] In addition, to achieve the above object, the present application also provides a storage medium, which is a computer-readable storage medium. A computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the formaldehyde removal method for buildings described above are implemented.

[0038] In addition, to achieve the above object, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the formaldehyde removal method for buildings described above are implemented.

[0039] One or more technical solutions proposed by the present application have at least the following technical effects:

[0040] Compared with the related technology that uses an air purifier with a formaldehyde decomposition function to remove formaldehyde within the building range and reduce the indoor formaldehyde concentration. However, this method can only treat pollutants in the air, that is, it can only remove free formaldehyde, and cannot directly act on the pollution source, resulting in low efficiency of removing formaldehyde within the building range. In contrast, the present application can determine the potential release source information of bound formaldehyde by obtaining the temperature distribution and surface images in the target area, and generate a targeted formaldehyde removal strategy accordingly. This method can reduce the release of formaldehyde from the source and fundamentally solve the formaldehyde pollution problem, rather than simply passively purifying formaldehyde in the air. That is, the present application can simultaneously treat the formaldehyde release source and formaldehyde in the air, thereby more comprehensively reducing the indoor formaldehyde concentration and improving the effect of removing formaldehyde within the building range. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0042] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0043] Figure 1 It is a schematic flowchart provided for the first embodiment of the formaldehyde removal method for buildings of the present application;

[0044] Figure 2 It is a schematic block diagram of the module structure of the formaldehyde removal device for buildings in the embodiments of the present application;

[0045] Figure 3 It is a schematic diagram of the device structure of the hardware operating environment involved in the formaldehyde removal method for buildings in the embodiments of the present application.

[0046] The realization of the object of the present application, its functional features and advantages will be further described in conjunction with embodiments with reference to the accompanying drawings. Specific Embodiments

[0047] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0048] To better understand the technical solutions of the present application, the following will be described in detail in conjunction with the accompanying drawings of the specification and specific embodiments.

[0049] The main solution of the embodiment of the present application is: when a start instruction is received, obtain the temperature distribution in the target area and the surface image of the target object; based on the temperature distribution, determine the potential release source information of bound formaldehyde; based on the surface image, determine the material information of the target object, and based on the material information, determine the release trend information of free formaldehyde; based on the release source information and the release trend information, generate a corresponding formaldehyde removal strategy, execute the formaldehyde removal strategy, and obtain a formaldehyde removal result.

[0050] In this embodiment, the formaldehyde removal device for buildings is used as the execution main body. For the convenience of description, hereinafter, it will be described simply as "device".

[0051] In the related art, usually an air purifier with a formaldehyde decomposition function is used to remove formaldehyde in the building area and reduce the indoor formaldehyde concentration. However, this method can only treat the pollutants in the air, that is, it can only remove free formaldehyde, and cannot directly act on the pollution source. Therefore, the effect of removing formaldehyde in the building area by this method is low.

[0052] The present application provides a solution to more comprehensively reduce the indoor formaldehyde concentration, thereby improving the effect of removing formaldehyde in the building area.

[0053] As can be seen from the above embodiments, the present application can determine the potential release source information of bound formaldehyde by obtaining the temperature distribution and surface image in the target area, and generate a targeted formaldehyde removal strategy accordingly. This method can reduce the release of formaldehyde from the source and fundamentally solve the formaldehyde pollution problem, rather than simply passively purifying the formaldehyde in the air. That is, the present application can simultaneously treat the formaldehyde release source and the formaldehyde in the air, thereby more comprehensively reducing the indoor formaldehyde concentration, and thus improving the effect of removing formaldehyde in the building area.

[0054] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication, and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device or a terminal system that can implement the above functions. Hereinafter, taking the formaldehyde removal device for buildings as an example, this embodiment and the following embodiments will be described.

[0055] Based on this, the embodiment of the present application provides a formaldehyde removal method for buildings. Refer to Figure 1 , Figure 1 which is a schematic flowchart of the first embodiment of the formaldehyde removal method for buildings of the present application.

[0056] In this embodiment, the formaldehyde removal method for buildings includes steps S100 to S400:

[0057] Step S100, when a start instruction is received, obtain the temperature distribution in the target area and the surface image of the target object;

[0058] In a specific implementation, when the device receives an instruction for the formaldehyde removal function, it measures and records the temperature distribution in the target area by means of infrared thermal imaging. The temperature distribution includes the temperature values at different positions in the target area, including the highest temperature, the lowest temperature, and the average temperature, etc. Specifically, the device can convert the temperature distribution on the surface of an object into a visual thermal image by using an infrared thermal imager, and different colors represent different temperatures.

[0059] It can be understood that infrared thermal imaging technology captures the infrared radiation emitted by an object and converts it into a visual thermal image. The higher the surface temperature of the object, the greater the intensity of the infrared radiation emitted, and the higher the brightness of the corresponding pixel points on the thermal image. The device can determine the position of the high-temperature area by analyzing the brightness distribution of the thermal image.

[0060] In a specific implementation, the device also takes a surface image of the target object to observe its appearance characteristics. Specifically, the device obtains the image of the object surface through a camera or other image acquisition devices. After collecting the image, the device uses image processing and deep learning algorithms to analyze the texture, color, gloss, and other characteristics in the image, so as to judge the material type of the furniture. For example, density boards usually have relatively uniform textures and lighter colors, while composite floors have more complex textures and richer color levels.

[0061] Step S200, based on the temperature distribution, determine the potential release source information of bound formaldehyde;

[0062] It should be noted that bound formaldehyde mainly exists inside decoration materials (such as artificial boards, adhesives, etc.), and its release is a slow process, usually affected by temperature. Research shows that an increase in temperature significantly promotes the release of formaldehyde. For example, when the indoor temperature exceeds 19°C, the release rate of formaldehyde will increase significantly. In the actual environment, the influence of temperature on formaldehyde release can be quantified by a temperature correction coefficient. For example, for every 1°C increase in temperature, the release rate of formaldehyde will increase by 0.1 to 0.25 times.

[0063] In specific implementation, the device obtains the temperature distribution in the target area by means of infrared thermal imaging technology, etc. For example, the device uses an infrared thermal imager to take a thermal image of the target area to determine which areas have a higher temperature. Specifically, the device analyzes the temperature distribution data using the existing formaldehyde release law and temperature correction model to determine which areas may be the sources of formaldehyde release. For example, if the temperature of a certain area is significantly higher than that of other areas, and there are a large number of materials (such as artificial boards) that may release formaldehyde in this area, it can be inferred that this area is a potential release source of bound formaldehyde.

[0064] In specific implementation, the steps for the device to determine the potential release source information of bound formaldehyde based on the temperature distribution include:

[0065] Based on the temperature distribution, determine the temperature change information of each area in the target area, where the temperature change information includes the temperature rise value and the rise time; based on the temperature rise value and the rise time, determine the formaldehyde release stage; based on a preset formaldehyde release law database and the formaldehyde release stage, match the temperature change information to obtain the potential release source information of bound formaldehyde.

[0066] In specific implementation, the device calculates the temperature rise value of each area in the target area through the temperature distribution data, which can be obtained by comparing the difference between the current temperature and the initial temperature. Further, the device also records the time required for the temperature to rise to the current value, which can be determined by monitoring the change of temperature over time.

[0067] In specific implementation, the device determines the stage of formaldehyde release according to the temperature rise value and the rise time. Specifically, formaldehyde release is usually divided into three stages: initial release, accelerated release, and stable release. The temperature rise value and the rise time can reflect the activity degree of formaldehyde release, thus helping to determine the release stage.

[0068] It should be noted that the formaldehyde release law database is a database containing formaldehyde release laws under different materials and different temperature conditions. By matching the temperature change information with the data in the database, the device can find the release law closest to the current situation. Specifically, the matching process can be that the device compares the temperature rise value and rise time of the target area with the data in the database to find the most matching release law, which can be achieved by calculating the similarity or using machine learning algorithms.

[0069] In a specific implementation, the device can obtain the corresponding formaldehyde release law according to the matching and determine the potential release sources of bound formaldehyde. This includes information such as the location, material, and release rate of the release source.

[0070] In a specific implementation, by analyzing the temperature distribution and formaldehyde release law, this application can effectively determine the potential release sources of bound formaldehyde and provide a scientific basis for indoor environmental governance. This method combines technologies such as temperature monitoring, formaldehyde release law analysis, and database matching, and has high practicability and accuracy.

[0071] Step S300, based on the surface image, determine the material information of the target object, and based on the material information, determine the release trend information of free formaldehyde;

[0072] In a specific implementation, by analyzing the surface image of the target object, the material type of the object (such as density board, composite floor, artificial board, etc.) is identified, and then according to the identified material information and combined with the known formaldehyde release law, the release trend of free formaldehyde of this material under the current environmental conditions is judged. Specifically, the device uses image recognition technology (such as convolutional neural network, etc.) to analyze the surface image of the target object to identify the material type of the object. The formaldehyde release characteristics of different materials are different. For example, artificial boards such as density boards and composite floors usually contain more formaldehyde.

[0073] Furthermore, the device combines the identified material information with the known formaldehyde release law (such as the influence of temperature and humidity on formaldehyde release) to judge the release trend of free formaldehyde of this material under the current environmental conditions. Free formaldehyde refers to the formaldehyde that has been released into the air, and its concentration is affected by factors such as material type, environmental temperature, and humidity.

[0074] In a specific implementation, the steps for the device to determine the material information of the target object based on the surface image and determine the release trend information of free formaldehyde based on the material information include:

[0075] Extract the feature information of the target object from the surface image; based on the feature information, identify the material information of the target object; based on a preset mapping database, match the material information to obtain the release trend information of free formaldehyde, where the mapping database includes mapping information between multiple object materials and release trends.

[0076] It should be noted that the surface image refers to the surface image of the target object obtained through a camera or other imaging device, and these images contain information such as the texture, color, and shape of the object.

[0077] In a specific implementation, the device uses image processing and analysis techniques to extract the feature information of the target object from the surface image. These features include but are not limited to texture features, color features, shape features, etc.

[0078] In a specific implementation, the device uses machine learning or deep learning algorithms (such as convolutional neural network, CNN) to identify the material of the target object according to the extracted feature information. For example, by analyzing texture and color features, materials such as wood, metal, and plastic can be distinguished. This usually requires a pre-trained model that has been trained on a large amount of labeled image data and can accurately identify different materials.

[0079] It should be noted that the mapping database is a preset database that contains the mapping relationship between different materials and the formaldehyde release trend. For example: Density board: Under the conditions of temperature 25°C and humidity 60%, the formaldehyde release rate is relatively high; Solid wood board: The formaldehyde release rate is relatively low; Composite floor: The formaldehyde release rate is medium.

[0080] In a specific implementation, the device matches the identified material information with the data in the mapping database to find the corresponding formaldehyde release trend information. For example, if the target object is identified as a density board, then according to the mapping database, the formaldehyde release trend of the density board under the current environmental conditions can be known.

[0081] It can be understood that the release trend information includes the formaldehyde release rate, release period, and the degree of influence by environmental factors (such as temperature, humidity), etc. Through this method, the present application can predict the concentration and trend of free formaldehyde that the target object may release under the current environmental conditions, thereby providing a scientific basis for indoor formaldehyde treatment.

[0082] Step S400, based on the release source information and the release trend information, generate a corresponding formaldehyde removal strategy, execute the formaldehyde removal strategy, and obtain the formaldehyde removal result.

[0083] In specific implementation, the device formulates targeted formaldehyde removal strategies based on the release source information and the release trend information. These strategies include, but are not limited to: ventilation strategy: if the formaldehyde release rate of the release source is high, the ventilation volume can be increased to accelerate the discharge of formaldehyde; heating treatment: for bound formaldehyde, its release can be accelerated by heating, and then removed in combination with ventilation or adsorption technology; chemical treatment: using formaldehyde decomposing agents or sealants to act directly on the release source to reduce formaldehyde release; photocatalyst treatment: spraying photocatalyst on the surface of the release source to decompose formaldehyde using ultraviolet light; air purifier: placing an air purifier near the release source to remove free formaldehyde through adsorption and catalytic decomposition technology.

[0084] In specific implementation, the device actually performs corresponding operations according to the generated formaldehyde removal strategies. Specifically, the present application provides a dynamic regulation strategy. For example, the device automatically switches the working mode according to the type of pollution source (free / bound): for high-concentration free formaldehyde, high-speed adsorption and catalytic decomposition are started; during the bound release period (such as when it is closed at night), local heating and photocatalyst circulation purification are turned on. Specifically at the execution level, the device uses an intelligent robotic arm to control the swing angle of the air intake component and the direction of the nozzle to accurately cover the pollution source (such as the gap of the wardrobe). The power consumption and purification efficiency of the ultraviolet lamp and the heating module can also be balanced through a reinforcement learning algorithm.

[0085] In specific implementation, after the device executes the formaldehyde removal strategy, it measures the change in the indoor formaldehyde concentration through a detection device (such as a formaldehyde detector) to evaluate the removal effect. Specifically, the device compares the formaldehyde concentrations before and after treatment to determine whether the formaldehyde has been effectively reduced; or checks whether the formaldehyde concentration near the release source has decreased significantly; or confirms whether the treatment measures have achieved the expected formaldehyde removal target.

[0086] That is to say, the present application formulates and executes corresponding formaldehyde removal strategies according to the determined formaldehyde release source information and release trend information, and finally evaluates the treatment effect to obtain the result of formaldehyde removal. This method can effectively reduce the indoor formaldehyde concentration and improve the indoor air quality through scientific analysis and targeted treatment measures.

[0087] In specific implementation, the steps for the device to generate corresponding formaldehyde removal strategies based on the release source information and the release trend information include:

[0088] Based on the release source information and the release trend information, parameter prediction is performed through a preset parameter adjustment model to obtain target parameters, where the target parameters include the heating temperature and the adsorption frequency. The parameter adjustment model is obtained by iteratively training a preset model to be trained based on release source information samples, release trend information samples, and corresponding parameter result labels; based on the heating temperature and the adsorption frequency, a formaldehyde removal strategy is formed.

[0089] In a specific implementation, the parameter adjustment model is a preset machine learning model used to predict target parameters (such as heating temperature and adsorption frequency) based on release source information and release trend information. That is, the device inputs the release source information and release trend information into the parameter adjustment model, and the model outputs the predicted target parameters. The target parameters include heating temperature, adsorption frequency, etc. These parameters are predicted based on the release source information and release trend information and are used to guide the implementation of the formaldehyde removal strategy.

[0090] That is, the device uses a machine learning model to predict target parameters (such as heating temperature and adsorption frequency) based on formaldehyde release source information and release trend information, and then formulates and executes a formaldehyde removal strategy based on these parameters. This method can more scientifically and accurately guide the formaldehyde removal work through data-driven parameter prediction, improving the treatment effect.

[0091] In a specific implementation, before the step of the device performing parameter prediction through a preset parameter adjustment model based on the release source information and the release trend information to obtain target parameters, the method includes:

[0092] Obtain an information sample set, the ambient light intensity information corresponding to the information sample set, and the parameter result label of the information sample set, where the information sample set includes release source information samples and release trend information samples; determine the ambient light weight based on the ambient light intensity information; and iteratively train a preset model to be trained based on the information sample set, the ambient light weight, and the parameter result label to obtain a parameter adjustment model.

[0093] It should be noted that the information sample set is a data set containing multiple samples, and each sample includes: a release source information sample, which is detailed information about the formaldehyde release source, such as the location of the release source, the material type (such as density board, composite floor, etc.), the area of the release source, etc.; a release trend information sample, which is information about the formaldehyde release trend, such as the formaldehyde release rate, release cycle, and the degree of influence by temperature and humidity.

[0094] In a specific implementation, for each sample, record its corresponding ambient light intensity. The light intensity affects the formaldehyde release rate (for example, photocatalytic technology accelerates the decomposition of formaldehyde under light conditions), so this is an important environmental factor.

[0095] It can be understood that the parameter result label is the "correct answer" corresponding to each sample, that is, the best parameter setting that has been verified in actual applications. For example, for a certain sample, the best heating temperature is 55 °C, and the best adsorption frequency is 3 times per hour. These labels are used to train the model so that it can learn how to predict the correct parameters based on the input release source information and release trend information.

[0096] In a specific implementation, the ambient light weight assigns a weight value to each sample according to the ambient light intensity information. This weight reflects the degree of influence of the light intensity on formaldehyde release and treatment. For example, if a certain sample has a high light intensity and it is known that the light intensity significantly affects formaldehyde release, then the light weight of this sample will be high.

[0097] In a specific implementation, the model to be trained is a preset machine learning model, such as a neural network, a support vector machine (SVM), or other regression models. The purpose of the model is to predict target parameters based on the input release source information and release trend information. Specifically, the device uses the information sample set, the ambient light weight, and the parameter result label to train the model. In each iteration, the model adjusts its own parameters according to the input sample information and weight to minimize the difference between the predicted value and the actual label. The ambient light weight affects the degree of attention the model pays to each sample, thus ensuring that the model can better learn the influence of light intensity on formaldehyde release and treatment.

[0098] It can be understood that the parameter adjustment model is the final model obtained after iterative training, and it can predict target parameters (such as heating temperature and adsorption frequency) based on new release source information and release trend information. This model can be used in the generation of formaldehyde removal strategies. That is, this application trains a model that can predict formaldehyde removal strategy parameters by collecting release source information samples, release trend information samples, and corresponding parameter result labels, and combining ambient light intensity information. This method can improve the scientificity and effectiveness of formaldehyde removal strategies, while considering the influence of environmental factors on formaldehyde release and treatment.

[0099] In a specific implementation, the steps of iteratively training a preset model to be trained based on the information sample set, the ambient light weight, and the parameter result label to obtain a parameter adjustment model include:

[0100] Input the information sample set and the ambient light weight into the preset model to be trained to obtain a predicted parameter result; calculate the difference between the predicted parameter result and the parameter result label to obtain an error result; based on the error result, determine whether the error result meets the error standard indicated by the preset error threshold range; if the error result does not meet the error standard indicated by the preset error threshold range, then return to the step of inputting the information sample set and the ambient light weight into the preset model to be trained to obtain a predicted parameter result, and stop training until the error result meets the error standard indicated by the preset error threshold range, and obtain a parameter adjustment model that meets the accuracy condition.

[0101] In a specific implementation, the model outputs prediction parameters based on the input information sample set and the environmental light weight, such as heating temperature and adsorption frequency.

[0102] In a specific implementation, the device calculates the difference between the prediction parameter result and the parameter result label to obtain an error result. This is usually achieved by calculating the mean squared error (MSE) or other error metrics.

[0103] It should be noted that the preset error threshold range is used to determine whether the prediction accuracy of the model meets the requirements. If the error result is within the preset error threshold range, it is considered that the prediction accuracy of the model meets the requirements. If the error result does not meet the error standard, it means that the prediction accuracy of the model is not high enough and needs to be further trained. Therefore, return the step of inputting the information sample set and the environmental light weight into the preset model to be trained to obtain the prediction parameter result, that is, input the information sample set and the environmental light weight into the model again to obtain a new prediction parameter result.

[0104] Finally, when the error result meets the error standard, it means that the prediction accuracy of the model has reached the requirements and the training can be stopped. The final model obtained after iterative training can predict the target parameters based on the new release source information and release trend information, and the prediction accuracy meets the preset error standard.

[0105] That is to say, the above describes an iterative training process of a machine learning model. By continuously adjusting the model parameters, the error between its prediction result and the actual label is minimized until the preset error standard is met. This method can ensure that the model has a high prediction accuracy, so as to generate an effective formaldehyde removal strategy in practical applications.

[0106] Compared with the related technology that uses an air purifier with a formaldehyde decomposition function to remove formaldehyde in the building range and reduce the indoor formaldehyde concentration. However, this method can only treat pollutants in the air, that is, only remove free formaldehyde, and cannot directly act on the pollution source, resulting in low efficiency in removing formaldehyde in the building range. In contrast, the present application can determine the potential release source information of bound formaldehyde by obtaining the temperature distribution and surface image in the target area, and generate a targeted formaldehyde removal strategy accordingly. This method can reduce the release of formaldehyde from the source and fundamentally solve the formaldehyde pollution problem, rather than just passively purifying formaldehyde in the air. That is, the present application can simultaneously treat the formaldehyde release source and formaldehyde in the air, thereby more comprehensively reducing the indoor formaldehyde concentration and improving the effect of removing formaldehyde in the building range.

[0107] The present application also provides a formaldehyde removal device for buildings. Please refer to Figure 2 , the formaldehyde removal device for buildings includes:

[0108] An acquisition module 10, configured to acquire the temperature distribution within a target area and the surface image of a target object when receiving a start instruction;

[0109] A release source information determination module 20, configured to determine the potential release source information of bound formaldehyde based on the temperature distribution;

[0110] A release trend determination module 30, configured to determine the material information of the target object based on the surface image, and determine the release trend information of free formaldehyde based on the material information;

[0111] A generation module 40, configured to generate a corresponding formaldehyde removal strategy based on the release source information and the release trend information, execute the formaldehyde removal strategy, and obtain a formaldehyde removal result.

[0112] Optionally, the release trend determination module 30 includes:

[0113] An extraction module, configured to extract the feature information of the target object from the surface image;

[0114] An identification module, configured to identify the material information of the target object based on the feature information;

[0115] A matching module, configured to match the material information based on a preset mapping database to obtain the release trend information of free formaldehyde, where the mapping database includes mapping information between multiple object materials and release trends.

[0116] Optionally, the release source information determination module 20 includes:

[0117] A temperature change information module, configured to determine the temperature change information of each area in the target area based on the temperature distribution, where the temperature change information includes a temperature rise value and a rise time;

[0118] A formaldehyde release stage determination module, configured to determine the formaldehyde release stage based on the temperature rise value and the rise time;

[0119] An information matching module, configured to match the temperature change information based on a preset formaldehyde release law database and the formaldehyde release stage to obtain the potential release source information of bound formaldehyde.

[0120] Optionally, the generation module 40 includes:

[0121] A prediction module, configured to perform parameter prediction through a preset parameter adjustment model based on the release source information and the release trend information, so as to obtain target parameters, where the target parameters include heating temperature and adsorption frequency, and the parameter adjustment model is obtained by iteratively training a preset model to be trained based on release source information samples, release trend information samples, and corresponding parameter result labels;

[0122] A composition module, configured to compose a formaldehyde removal strategy based on the heating temperature and the adsorption frequency.

[0123] Optionally, the formaldehyde removal device for buildings further includes:

[0124] A sample acquisition module, configured to acquire an information sample set, environmental light intensity information corresponding to the information sample set, and parameter result labels of the information sample set, where the information sample set includes release source information samples and release trend information samples;

[0125] An environmental light weight determination module, configured to determine an environmental light weight based on the environmental light intensity information;

[0126] A training module, configured to iteratively train a preset model to be trained based on the information sample set, the environmental light weight, and the parameter result labels, so as to obtain a parameter adjustment model.

[0127] Optionally, the training module includes:

[0128] A parameter prediction module, configured to input the information sample set and the environmental light weight into a preset model to be trained, so as to obtain a predicted parameter result;

[0129] A difference calculation module, configured to calculate the difference between the predicted parameter result and the parameter result labels, so as to obtain an error result;

[0130] A judgment module, configured to judge whether the error result meets an error standard indicated by a preset error threshold range based on the error result;

[0131] An iterative training module, configured to, if the error result does not meet the error standard indicated by the preset error threshold range, return to the step of inputting the information sample set and the environmental light weight into a preset model to be trained to obtain a predicted parameter result, and stop training until the error result meets the error standard indicated by the preset error threshold range, so as to obtain a parameter adjustment model meeting the accuracy condition.

[0132] The formaldehyde removal device for buildings provided by the present application adopts the formaldehyde removal method for buildings in the above embodiment, and can solve the technical problems of formaldehyde removal for buildings. Compared with the prior art, the beneficial effects of the formaldehyde removal device for buildings provided by the present application are the same as those of the formaldehyde removal method for buildings provided by the above embodiment, and the other technical features in the formaldehyde removal device for buildings are the same as the features disclosed in the above embodiment method, which will not be elaborated here.

[0133] The present application provides a formaldehyde removal device for buildings. The formaldehyde removal device for buildings includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the formaldehyde removal method for buildings in Embodiment 1 above.

[0134] Refer to the following Figure 3 , which shows a schematic structural diagram of a formaldehyde removal device for buildings suitable for implementing the embodiments of the present application. The formaldehyde removal device for buildings in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions: tablet computers), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The formaldehyde removal device for buildings shown is only an example, and should not impose any limitations on the functions and usage scopes of the embodiments of the present application.

[0135] As shown in Figure 3As shown, the formaldehyde removal device for buildings may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 into the random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the formaldehyde removal device for buildings are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. The input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the formaldehyde removal device for buildings to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows a formaldehyde removal device for buildings with various systems, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems may be implemented or had alternatively.

[0136] Particularly, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from the network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above functions defined in the methods of the embodiments disclosed in the present application are executed.

[0137] The formaldehyde removal device for buildings provided by the present application adopts the formaldehyde removal method for buildings in the above embodiments, and can solve the technical problems of formaldehyde removal for buildings. Compared with the prior art, the beneficial effects of the formaldehyde removal device for buildings provided by the present application are the same as those of the formaldehyde removal method for buildings provided in the above embodiments, and the other technical features in the formaldehyde removal device for buildings are the same as the features disclosed in the method of the previous embodiment, and will not be elaborated here.

[0138] It should be understood that each part disclosed in this application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0139] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0140] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the formaldehyde removal method for buildings in the above embodiments.

[0141] The computer-readable storage medium provided by this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, device, or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0142] The above computer-readable storage medium can be included in the formaldehyde removal device for buildings; it can also exist separately without being assembled into the formaldehyde removal device for buildings.

[0143] The above computer-readable storage medium carries one or more programs, and when the one or more programs are executed by the formaldehyde removal device for buildings, the formaldehyde removal device for buildings is caused to: remove formaldehyde for buildings.

[0144] Computer program code for performing the operations of the present application may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it may be connected to an external computer (e.g., by connecting through the Internet using an Internet service provider).

[0145] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0146] The modules described in the embodiments of the present application may be implemented in software or in hardware. In some cases, the name of the module does not constitute a limitation on the unit itself.

[0147] The readable storage medium provided by the present application is a computer-readable storage medium that stores computer-readable program instructions (i.e., computer programs) for performing the above-mentioned formaldehyde removal method for buildings, and can solve the technical problems of formaldehyde removal for buildings. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as those of the formaldehyde removal method for buildings provided by the above embodiments, and will not be elaborated here.

[0148] The present application also provides a computer program product, including a computer program which, when executed by a processor, implements the steps of the formaldehyde removal method for buildings as described above.

[0149] The computer program product provided by the present application can solve the technical problems of formaldehyde removal for buildings. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the formaldehyde removal method for buildings provided in the above embodiments, and will not be elaborated here.

[0150] The above are only some embodiments of the present application, and thus do not limit the patent scope of the present application. Any equivalent structural transformation made by using the content of the specification and drawings of the present application under the technical concept of the present application, or any direct / indirect application in other related technical fields, is included in the patent protection scope of the present application.

Claims

1. A formaldehyde removal method for construction, characterized in that, The method for removing formaldehyde for construction includes: Upon receiving a start instruction, obtaining the temperature distribution in the target area and the surface image of the target object; Based on the temperature distribution, determining the potential release source information of bound formaldehyde; Based on the surface image, determining the material information of the target object, and based on the material information, determining the release trend information of free formaldehyde; Based on the release source information and the release trend information, generating a corresponding formaldehyde removal strategy, executing the formaldehyde removal strategy, and obtaining a formaldehyde removal result.

2. The formaldehyde removal method for construction according to claim 1, wherein, The step of, based on the surface image, determining the material information of the target object, and based on the material information, determining the release trend information of free formaldehyde, includes: Extracting the feature information of the target object from the surface image; Based on the feature information, identifying the material information of the target object; Based on a preset mapping database, matching the material information to obtain the release trend information of free formaldehyde, where the mapping database includes mapping information between multiple object materials and release trends.

3. The formaldehyde removal method for buildings according to claim 1, wherein, The step of, based on the temperature distribution, determining the potential release source information of bound formaldehyde, includes: Based on the temperature distribution, determining the temperature change information of each area in the target area, where the temperature change information includes the temperature rise value and the rise time; Based on the temperature rise value and the rise time, determining the formaldehyde release stage; Based on a preset formaldehyde release rule database and the formaldehyde release stage, matching the temperature change information to obtain the potential release source information of bound formaldehyde.

4. The formaldehyde removal method for construction according to claim 1, characterized in that, The step of, based on the release source information and the release trend information, generating a corresponding formaldehyde removal strategy, includes: Based on the release source information and the release trend information, performing parameter prediction through a preset parameter adjustment model to obtain target parameters, where the target parameters include the heating temperature and the adsorption frequency, and the parameter adjustment model is obtained by iteratively training a preset model to be trained based on release source information samples, release trend information samples, and corresponding parameter result labels; Based on the heating temperature and the adsorption frequency, forming a formaldehyde removal strategy.

5. The formaldehyde removal method for buildings according to claim 4, characterized in that, Before the step of, based on the release source information and the release trend information, performing parameter prediction through a preset parameter adjustment model to obtain target parameters, the method includes: Obtaining an information sample set, the environmental light intensity information corresponding to the information sample set, and the parameter result labels of the information sample set, where the information sample set includes release source information samples and release trend information samples; Based on the environmental light intensity information, determining the environmental light weight; Based on the information sample set, the environmental light weight, and the parameter result labels, iteratively training a preset model to be trained to obtain a parameter adjustment model.

6. The formaldehyde removal method for buildings according to claim 5, characterized in that, The step of, based on the information sample set, the environmental light weight, and the parameter result labels, iteratively training a preset model to be trained to obtain a parameter adjustment model, includes: Input the information sample set and the environmental light weight into a preset model to be trained to obtain a prediction parameter result; Calculate the difference between the prediction parameter result and the parameter result label to obtain an error result; Based on the error result, determine whether the error result meets the error standard indicated by a preset error threshold range; If the error result does not meet the error standard indicated by the preset error threshold range, return to the step of inputting the information sample set and the environmental light weight into a preset model to be trained to obtain a prediction parameter result, and stop training until the error result meets the error standard indicated by the preset error threshold range, so as to obtain a parameter adjustment model that meets the accuracy condition.

7. A formaldehyde removal device for buildings, characterized in that, The device includes: An acquisition module, configured to acquire the temperature distribution in a target area and the surface image of a target object when a start instruction is received; A release source information determination module, configured to determine the potential release source information of bound formaldehyde based on the temperature distribution; A release trend determination module, configured to determine the material information of the target object based on the surface image, and determine the release trend information of free formaldehyde based on the material information; A generation module, configured to generate a corresponding formaldehyde removal strategy based on the release source information and the release trend information, execute the formaldehyde removal strategy, and obtain a formaldehyde removal result.

8. An apparatus for removing formaldehyde in buildings, characterized in that, The device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the computer program is configured to implement the steps of the formaldehyde removal method for buildings according to any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the formaldehyde removal method for buildings according to any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program, and when the computer program is executed by a processor, it implements the steps of the formaldehyde removal method for buildings according to any one of claims 1 to 6.

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