A kind of intelligent mirror cleaning method and device of Internet of Things

Abstract

The present invention relates to the field of mirror cleaning technology, and discloses a smart mirror cleaning method and device of the Internet of Things, including: receiving a cleaning instruction, confirming a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, obtaining one or more first cleaning areas based on the smart mirror, fitting one or more cleaning schemes using the one or more first cleaning areas, obtaining a target cleaning scheme according to the one or more cleaning schemes, performing a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initial cleaned smart mirror, confirming that the initial cleaned smart mirror is a target cleaned smart mirror, obtaining a cleaning report based on the target cleaned smart mirror, and sending the cleaning report to the initiator of the cleaning instruction to achieve cleaning of the smart mirror. The main purpose of the present invention is to solve the problem of high limitations and high energy consumption when cleaning the surface of a smart mirror.

Description

Technical Field

[0001] The invention relates to an intelligent mirror cleaning method and device for the Internet of Things, and belongs to the technical field of mirror cleaning. Background Art

[0002] With the development of technology, more and more smart mirrors are put on the market. The effect that a smart mirror can present is not only related to the resolution of the screen in the smart mirror, but also to the cleanliness of the smart mirror surface. Correspondingly, whether the smart mirror surface can be cleaned intelligently is particularly important.

[0003] At present, the cleaning of the surface of smart mirrors is mostly done manually.

[0004] Although the above method can realize the cleaning of the mirror surface of the smart mirror, before performing the cleaning operation on the mirror surface of the smart mirror, it mostly relies on human experience to judge whether the mirror surface of the smart mirror needs to be cleaned, and the cleaning operation is usually performed on the entire mirror surface of the smart mirror. Therefore, there are problems such as high limitations and high energy consumption when cleaning the mirror surface of the smart mirror. Summary of the invention

[0005] The present invention provides an intelligent mirror cleaning method, device and computer-readable storage medium of the Internet of Things, the main purpose of which is to solve the problems of high limitations and high energy consumption when cleaning the surface of an intelligent mirror.

[0006] To achieve the above object, the present invention provides an intelligent mirror cleaning method for the Internet of Things, comprising:

[0007] Receiving a cleaning instruction, and confirming a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a cleaning agent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit, and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area;

[0008] Acquiring one or more first cleaning areas based on the smart mirror, wherein acquiring one or more first cleaning areas based on the smart mirror comprises:

[0009] Performing a region division operation on the smart mirror based on a pre-built division model to obtain a plurality of initial detection regions, wherein an area corresponding to each initial detection region is equal to an area threshold corresponding to the division model, and the shape corresponding to the division model is preset to be a rectangle, wherein the division model is related to a target cleaning region that can be formed by a cleaning mechanism into one or more rectangles;

[0010] Sequentially extracting initial detection areas from the multiple initial detection areas, and performing the following operations on the extracted initial detection areas:

[0011] Performing a marking operation on the extracted initial detection area to obtain a marked detection area, and summarizing the marked detection area to obtain a marked detection area set;

[0012] Extracting the marker detection areas from the marker detection area set in sequence, and performing the following operations on the extracted marker detection areas:

[0013] Acquire a detection image based on the extracted identification detection area, perform a grayscale operation on the detection image to obtain a grayscale image, obtain a grayscale threshold for segmentation, and use a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image, wherein the grayscale value required by the region growing algorithm is preset as the grayscale threshold;

[0014] Summarizing the stain images to obtain a stain image set, and acquiring one or more first clean areas based on the stain image set, wherein the stain image set includes one or more stain images, and the one or more first clean areas correspond to the one or more stain images in a one-to-one manner;

[0015] Using the one or more first cleaning regions to fit one or more cleaning schemes includes: sequentially extracting one of the one or more first cleaning regions, and performing the following operations on the extracted first cleaning region:

[0016] The second search area is obtained by using the extracted first cleaning area, wherein the second search area is a first cleaning area adjacent to the extracted first cleaning area, and the extracted first cleaning area is eliminated from one or more first cleaning areas, and the second search area is used as the extracted first cleaning area, and the step of obtaining the second search area by using the extracted first cleaning area is returned to until the second search area cannot be obtained by using the extracted first cleaning area, and one or more initial cleaning areas are obtained;

[0017] Sequentially extracting initial cleaning regions from the one or more initial cleaning regions, and performing the following operations on the extracted initial cleaning regions:

[0018] One or more cleaning solutions are obtained based on the extracted initial cleaning area, wherein the one or more cleaning solutions are as follows:

[0019] Cleaning solution 1: performing a cleaning operation on each first cleaning area in the extracted initial cleaning area;

[0020] Cleaning scheme 2: obtaining one or more second cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more second cleaning schemes includes: one or more second cleaning areas, and the second cleaning scheme is composed of the second cleaning area and R first cleaning areas, wherein R is an integer greater than or equal to 0, and the area corresponding to the second cleaning area in the one or more second cleaning areas is greater than the area threshold;

[0021] Cleaning scheme three: obtaining one or more third cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more third cleaning schemes includes: one or more third cleaning areas, and the third cleaning scheme is composed of Q first cleaning areas, P second cleaning areas, and a third cleaning area, wherein Q and P are both integers greater than or equal to 0, and the third cleaning area in the one or more third cleaning areas includes the detection area corresponding to the detection image except the first cleaning area;

[0022] The one or more cleaning schemes are composed of cleaning scheme one, one or more second cleaning schemes corresponding to cleaning scheme two, and one or more third cleaning schemes corresponding to cleaning scheme three;

[0023] Obtaining a target cleaning scheme according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme requiring the least energy consumption;

[0024] Performing a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initially cleaned smart mirror;

[0025] After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror, and the cleaning report is sent to an initiator of a cleaning instruction to achieve cleaning of the smart mirror.

[0026] Optionally, the using a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image includes:

[0027] Detecting a target image from a grayscale image using a region growing algorithm, wherein the grayscale values ​​corresponding to the target image are all greater than or equal to the grayscale threshold;

[0028] If the target image exists, the target area of ​​the target image is obtained, and if the target area is greater than or equal to a preset grayscale area threshold, it is confirmed that the grayscale image corresponding to the target image is a stain image.

[0029] Optionally, obtaining a grayscale threshold for segmentation includes:

[0030] A reference image set is obtained as a reference, wherein the reference image set includes a plurality of reference images, reference images are extracted from the reference image set in sequence, and the following operations are performed on the extracted reference images:

[0031] A grayscale operation is performed on the extracted reference image to obtain a grayscale reference image, the grayscale reference images are summarized to obtain a grayscale reference image set, and the grayscale threshold is calculated using a pre-constructed grayscale threshold relationship and the grayscale reference image set, wherein the grayscale threshold relationship is as follows:

[0032]

[0033] Where G represents the grayscale threshold, represents the parameters of the kth grayscale reference image in the grayscale reference image set during calculation, e j represents the grayscale value of the jth pixel in the kth grayscale reference image of the grayscale reference image set, D represents the total number of D grayscale values ​​in the kth grayscale reference image of the grayscale reference image set, and p k represents the coefficient of the preset k-th grayscale reference image, F represents that there are F grayscale reference images in the grayscale reference image set, and

[0034] Optionally, obtaining a target cleaning scheme according to the one or more cleaning schemes includes:

[0035] Extract cleaning schemes from the one or more cleaning schemes in sequence, and perform the following operations on the extracted cleaning schemes:

[0036] The energy consumption evaluation value is calculated using the pre-built energy consumption evaluation relationship and the extracted cleaning plan, where the energy consumption evaluation relationship is as follows:

[0037]

[0038] Among them, Z represents the energy consumption evaluation value during cleaning, n represents a total of n target cleaning areas, x i It means that there are x target cleaning areas of type i, f i The expression relationship for the total energy consumption required when cleaning the i-th target cleaning area is expressed as follows: i represents the energy consumption of the cleaning unit when cleaning the i-th target cleaning area, v i represents the energy consumption of the cleaning unit when cleaning the i-th target cleaning area, a i represents the energy consumption of the drying unit when cleaning the i-th target cleaning area, b irepresents the energy consumption required by the detergent spraying unit when cleaning the i-th target cleaning area, y represents the energy consumption required by the mobile cleaning mechanism when cleaning, and the target cleaning area is composed of one or more first cleaning areas, one or more second cleaning areas, and one or more third cleaning areas;

[0039] The energy consumption evaluation values ​​are summarized to obtain an energy consumption evaluation value set, and a target cleaning solution is obtained based on the energy consumption evaluation value set.

[0040] Optionally, performing a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initially cleaned smart mirror includes:

[0041] Extracting target cleaning areas from the target cleaning scheme in sequence, and performing the following operations on the extracted target cleaning areas;

[0042] Using the cleaning unit to perform a wetting operation on the extracted target cleaning area to obtain a wet area, wherein the execution time of the wetting operation is preset, using the cleaning agent spraying unit to spray a pre-constructed cleaning agent on the wet area to obtain a first cleaning area, and based on the cleaning unit performing a cleaning operation on the first cleaning area to obtain a second cleaning area;

[0043] A third cleaning area is obtained based on the second cleaning area, the cleaning unit, the cleaning unit, the waste liquid guiding unit and the waste liquid collecting unit, and the drying unit is used to perform a drying operation on the third cleaning area to obtain an initially cleaned smart mirror.

[0044] Optionally, the confirming that the initially cleaned smart mirror is a target cleaned smart mirror comprises:

[0045] Acquire a second stain image set based on the initial cleaning smart mirror, wherein the second stain image set includes one or more second stain images, and acquire one or more marked cleaning areas based on the second stain image set, wherein the one or more second stain images correspond one-to-one to the one or more marked cleaning areas;

[0046] The initially cleaned smart mirror is identified as a target cleaned smart mirror based on the one or more identified cleaning areas.

[0047] Optionally, the confirming, based on the one or more identified cleaning areas, that the initially cleaned smart mirror is a target cleaned smart mirror comprises:

[0048] The one or more marked cleaning areas are used as one or more first cleaning areas, and a drying detection image set is acquired using a pre-built cycle experiment, a drying unit, and one or more first cleaning areas, wherein the number of executions of the cycle experiment is preset, and the cycle experiment is: returning to the step of acquiring one or more first cleaning areas based on the stain image set, the drying detection image set includes one or more drying detection images, and the one or more drying detection images correspond to the one or more first cleaning areas one by one;

[0049] Extracting drying detection images from the drying detection image set in sequence, and performing the following operations on the extracted drying detection images:

[0050] If the extracted drying detection image is not the second stain image or the cumulative number of executions of the cycle experiment is the number of executions, then the initially cleaned smart mirror is confirmed to be the target cleaned smart mirror.

[0051] In order to solve the above problems, the present invention also provides an intelligent mirror cleaning device of the Internet of Things, the device comprising:

[0052] An instruction receiving and environment confirmation module, used for receiving a cleaning instruction and confirming a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a detergent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area;

[0053] A cleaning scheme acquisition module is used to acquire one or more first cleaning areas based on the smart mirror, wherein acquiring one or more first cleaning areas based on the smart mirror includes:

[0054] Performing a region division operation on the smart mirror based on a pre-built division model to obtain a plurality of initial detection regions, wherein an area corresponding to each initial detection region is equal to an area threshold corresponding to the division model, and the shape corresponding to the division model is preset to be a rectangle, wherein the division model is related to a target cleaning region that can be formed by a cleaning mechanism into one or more rectangles;

[0055] Sequentially extracting initial detection areas from the multiple initial detection areas, and performing the following operations on the extracted initial detection areas:

[0056] Performing a marking operation on the extracted initial detection area to obtain a marked detection area, and summarizing the marked detection area to obtain a marked detection area set;

[0057] Extracting the marker detection areas from the marker detection area set in sequence, and performing the following operations on the extracted marker detection areas:

[0058] Acquire a detection image based on the extracted identification detection area, perform a grayscale operation on the detection image to obtain a grayscale image, obtain a grayscale threshold for segmentation, and use a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image, wherein the grayscale value required by the region growing algorithm is preset as the grayscale threshold;

[0059] Summarizing the stain images to obtain a stain image set, and acquiring one or more first clean areas based on the stain image set, wherein the stain image set includes one or more stain images, and the one or more first clean areas correspond to the one or more stain images in a one-to-one manner;

[0060] Fitting one or more cleaning schemes using the one or more first cleaning areas comprises: extracting one of the first cleaning areas in turn from the one or more first cleaning areas, and performing the following operations on the extracted first cleaning areas: obtaining a second search area using the extracted first cleaning area, wherein the second search area is a first cleaning area adjacent to the extracted first cleaning area, and excluding the extracted first cleaning area from one or more first cleaning areas, and taking the second search area as the extracted first cleaning area, returning to the step of obtaining the second search area using the extracted first cleaning area until the second search area cannot be obtained using the extracted first cleaning area, thereby obtaining one or more initial cleaning areas; extracting initial cleaning areas in turn from the one or more initial cleaning areas, and performing the following operations on the extracted initial cleaning areas: obtaining one or more cleaning schemes based on the extracted initial cleaning area, wherein the one or more cleaning schemes are as follows: Cleaning scheme 1: obtaining the second search area using the extracted first cleaning area Perform a cleaning operation on each first cleaning area in the extracted initial cleaning area; Cleaning scheme two: obtain one or more second cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more second cleaning schemes includes: one or more second cleaning areas, and the second cleaning scheme is composed of the second cleaning area and R first cleaning areas, wherein R is an integer greater than or equal to 0, and the area corresponding to the second cleaning area in the one or more second cleaning areas is greater than the area threshold; Cleaning scheme three: obtain one or more third cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more third cleaning schemes includes: one or more third cleaning areas, and the third cleaning area is composed of Q first cleaning areas and P second cleaning areas and a third cleaning area, wherein Q and P are both integers greater than or equal to 0, and the third cleaning area in the one or more third cleaning areas includes the detection area corresponding to the detection image except the first cleaning area;

[0061] The one or more cleaning schemes are composed of cleaning scheme one, one or more second cleaning schemes corresponding to cleaning scheme two, and one or more third cleaning schemes corresponding to cleaning scheme three;

[0062] A target cleaning scheme confirmation module, used to obtain a target cleaning scheme according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme requiring the least energy consumption;

[0063] A target cleaning scheme execution and feedback module, used to perform a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initially cleaned smart mirror;

[0064] After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror, and the cleaning report is sent to an initiator of a cleaning instruction to achieve cleaning of the smart mirror.

[0065] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0066] at least one processor; and,

[0067] a memory communicatively connected to the at least one processor; wherein,

[0068] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the above-mentioned intelligent mirror cleaning method of the Internet of Things.

[0069] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned intelligent mirror cleaning method of the Internet of Things.

[0070] Compared with the problems described in the background technology, the present invention first receives a cleaning instruction, and confirms a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a detergent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area. It can be seen that the present invention proposes an environment for cleaning the smart mirror when considering the cleaning of the smart mirror. The proposed cleaning mechanism can achieve directional cleaning of the smart mirror, and will not affect other areas that do not need to be cleaned during cleaning. Based on the smart mirror, one or more first cleaning areas are obtained, one or more cleaning schemes are fitted using the one or more first cleaning areas, and a target cleaning scheme is obtained according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme requiring the minimum energy consumption. It can be seen that the present invention first divides the smart mirror into a plurality of independently cleanable units, and can combine a plurality of independently cleanable units, thereby improving the feasibility of the present invention. Secondly, the present invention obtains a cleaning scheme requiring the minimum energy consumption from one or more cleaning schemes, and before formulating a cleaning scheme, uses image processing technology to perform recognition operations on the smart mirror, thereby identifying where the smart mirror needs to perform a cleaning operation as planned, thereby achieving directional cleaning of the smart mirror, and further solving the problem of high energy consumption required when cleaning the smart mirror. The cleaning mechanism and the target cleaning scheme are used to perform a cleaning operation on the smart mirror to obtain an initially cleaned smart mirror. After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror. It can be seen that the present invention, when cleaning the smart mirror, also considers that the stains to be cleaned may require multiple cleanings to remove, or that there may be special circumstances on the mirror surface of the smart mirror, which may result in the inability to remove the stains identified therein, and generates a cleaning report to improve the feasibility of the present invention. Therefore, the main purpose of the smart mirror cleaning method, device, electronic device and computer-readable storage medium of the Internet of Things proposed by the present invention is to solve the problems of high limitations and high energy consumption when cleaning the mirror surface of the smart mirror. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 A schematic diagram of a flow chart of an intelligent mirror cleaning method for the Internet of Things provided by an embodiment of the present invention;

[0072] Figure 2 A functional module diagram of an intelligent mirror cleaning device for the Internet of Things provided by an embodiment of the present invention;

[0073] Figure 3 A schematic structural diagram of an electronic device for implementing the intelligent mirror cleaning method of the Internet of Things provided by an embodiment of the present invention.

[0074] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0075] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0076] The embodiment of the present application provides an intelligent mirror cleaning method for the Internet of Things. The execution subject of the intelligent mirror cleaning method for the Internet of Things includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the intelligent mirror cleaning method for the Internet of Things can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0077] Embodiment 1:

[0078] Reference Figure 1 FIG. 1 is a flow chart of an intelligent mirror cleaning method for an Internet of Things provided by an embodiment of the present invention. In this embodiment, the intelligent mirror cleaning method for an Internet of Things includes:

[0079] S1. Receive a cleaning instruction, and confirm a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a detergent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit, and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area.

[0080] It should be understood that the cleaning instruction is an instruction issued to execute a cleaning operation on a specific smart mirror, and the cleaning environment is a necessary environment for executing the cleaning operation on the smart mirror. For example, a company has produced a batch of smart mirrors and now needs to package the smart mirrors. Therefore, it is required that there should be no dust or other stains on the mirror surface of the smart mirror. Xiao Wang is the mirror cleaner of the company, and Xiao Wang issues the cleaning instruction and confirms the cleaning environment.

[0081] Further, the detection unit is a unit for detecting the mirror surface of the smart mirror with stains. For the specific application of this unit, please refer to the subsequent embodiments. The detergent spraying unit is a unit for spraying detergent to the target cleaning area. Optionally, the detergent spraying unit is: a conduit with a nozzle. The cleaning unit is a unit for performing a cleaning operation on the target cleaning area. Optionally, the cleaning unit is a scraper. The same effect can be achieved by using other technologies, which will not be repeated here. The drying unit is used to perform a drying operation on the cleaned target cleaning area. The use of the drying unit can avoid secondary contamination of the cleaned target cleaning area and can better display the stains that have not been cleaned. Optionally, the drying unit is a hot fan of hot air output by the conduit. The same effect can be achieved by using other technologies, which will not be repeated here. The cleaning unit is used to clean the surface of the smart mirror. Optionally, the cleaning unit is a conduit with a nozzle. The difference from the detergent spraying unit is that the liquid sprayed by the cleaning unit is: water. The same effect can be achieved by using other technologies, which will not be repeated here. The waste liquid guiding unit is used to guide the waste liquid generated during cleaning to the waste liquid collecting unit. Optionally, the waste liquid guiding unit is a V-shaped groove with a slope, and the waste liquid collecting unit is a conduit. Other technologies can achieve the same effect, which will not be repeated here.

[0082] It should be explained that the cleaning mechanism will form a corresponding target cleaning area according to the proposed cleaning area. The purpose is: to achieve directional cleaning of a certain area in the smart mirror in combination with the actual situation, and after cleaning, the rest of the mirror surface of the smart mirror that does not need to be cleaned will not be contaminated due to the cleaning operation. Optionally, a guide rail combined with a micro-hydraulic mechanism is used to achieve this effect. Other technologies can achieve the same effect, which will not be repeated here. For example: the size of the smart mirror is a 3×3 rectangular area, and the smart mirror is divided into 9 areas with 1×1 as a unit. Among them, the cleaning area is a 1×1 area at the center of the smart mirror. The guide rail is used to realize the lateral and longitudinal movement of the cleaning mechanism. When the cleaning mechanism is located in the cleaning area, the micro-hydraulic mechanism is used to fix the cleaning mechanism to the cleaning area. The area enclosed by the cleaning mechanism on the surface of the smart mirror is the target cleaning area.

[0083] S2. Acquire one or more first cleaning areas based on the smart mirror, and fit one or more cleaning solutions using the one or more first cleaning areas.

[0084] Further, the acquiring one or more first cleaning areas based on the smart mirror includes:

[0085] Performing a region division operation on the smart mirror based on a pre-built division model to obtain a plurality of initial detection regions, wherein an area corresponding to each initial detection region is equal to an area threshold corresponding to the division model, and the shape corresponding to the division model is preset to be a rectangle, wherein the division model is related to a target cleaning region that can be formed by a cleaning mechanism into one or more rectangles;

[0086] Sequentially extracting initial detection areas from the multiple initial detection areas, and performing the following operations on the extracted initial detection areas:

[0087] Performing a marking operation on the extracted initial detection area to obtain a marked detection area, and summarizing the marked detection area to obtain a marked detection area set;

[0088] Extracting the marker detection areas from the marker detection area set in sequence, and performing the following operations on the extracted marker detection areas:

[0089] Acquire a detection image based on the extracted identification detection area, perform a grayscale operation on the detection image to obtain a grayscale image, obtain a grayscale threshold for segmentation, and use a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image, wherein the grayscale value required by the region growing algorithm is preset as the grayscale threshold;

[0090] The stain images are aggregated to obtain a stain image set, and one or more first clean regions are acquired based on the stain image set, wherein the stain image set includes one or more stain images, and the one or more first clean regions correspond to the one or more stain images in a one-to-one manner.

[0091] Furthermore, the partition model is a model with a proposed area and a rectangular shape, and its purpose is to divide the mirror surface of the smart mirror in combination with the target cleaning area that can be formed by the actual cleaning mechanism, so as to achieve more accurate directional cleaning. For example: the size of the smart mirror is a rectangular area of ​​3×3, and the smallest target cleaning area that can be formed by the cleaning mechanism is an area of ​​1×1, that is, the area threshold. Therefore, the smart mirror is divided into 9 areas with 1×1 as a unit, wherein each 1×1 area is an initial detection area, and if only one of the 9 areas is contaminated, the cleaning mechanism can achieve directional cleaning of the contaminated area. For ease of understanding, the 9 areas are expressed in the form of coordinates and the 9 areas are marked to obtain 9 marked detection areas. The marked detection area set is composed of 9 marked detection areas, wherein (1, 1) represents the first marked detection area, (1, 2) represents the second marked detection area, (1, 3) represents the third marked detection area, and so on, (3, 3) represents the ninth marked detection area. The purpose of marking the initial detection area is to more clearly and specifically know that a cleaning operation has been performed on a stain, and to accurately provide feedback on the stain if an abnormality occurs there. For more specific implementation methods, please refer to the following embodiments.

[0092] It should be understood that the detection image is an image obtained from the identification detection area, and the image is an image used to characterize whether there is a stain on the surface of the identification detection area. For example, the detection image is collected in the identification detection area using polarization filter technology. The purpose of acquiring the detection image is to eliminate the interference of stain detection caused by the light emitted by the mirror surface of the smart mirror. The grayscale operation refers to the operation of converting a color image into a grayscale image. This technology is a prior art and will not be repeated here. The color of the stain on the surface of the smart mirror is usually white. For example, water stains or dust deposited on the surface of the smart mirror appear as white stains. Since the generation of stains is often not a single one, but multiple stains are generated together, therefore, in the embodiment of the present invention, the area corresponding to the division model is used as the minimum unit for cleaning. For example, in the actual use process, the water stains generated during use cause pollution to the smart mirror, and the pollution caused by the water stains is often more than one place. By dividing the area corresponding to the model as the unit for cleaning, the energy consumption required for obtaining the stain position and the energy consumption required for cleaning the stain are saved.

[0093] It should be explained that the step of obtaining the grayscale threshold for segmentation includes:

[0094] A reference image set is obtained as a reference, wherein the reference image set includes a plurality of reference images, reference images are extracted from the reference image set in sequence, and the following operations are performed on the extracted reference images:

[0095] A grayscale operation is performed on the extracted reference image to obtain a grayscale reference image, the grayscale reference images are summarized to obtain a grayscale reference image set, and the grayscale threshold is calculated using a pre-constructed grayscale threshold relationship and the grayscale reference image set, wherein the grayscale threshold relationship is as follows:

[0096]

[0097] Where G represents the grayscale threshold, represents the parameters of the kth grayscale reference image in the grayscale reference image set during calculation, e j represents the grayscale value of the jth pixel in the kth grayscale reference image of the grayscale reference image set, D represents the total number of D grayscale values ​​in the kth grayscale reference image of the grayscale reference image set, and p k represents the coefficient of the preset k-th grayscale reference image, F represents that there are F grayscale reference images in the grayscale reference image set, and

[0098] It is understandable that the color of the stains formed on the smart mirror is often not uniform. Therefore, the reference image set and the grayscale threshold relationship are used to calculate whether the detection image contains stains, thereby improving the accuracy of stain judgment and avoiding the problem of too broad definition of stain judgment due to unreasonable grayscale threshold setting, thereby saving the resources required for cleaning the smart mirror. The reference image is an image of the stain that can be judged as a stain on the surface of the smart mirror in real life. The method of obtaining the reference image is the same as the method of obtaining the detection image, and can achieve the same effect, which will not be repeated here. For example: in real life, water droplets mixed with mud and dirt appear on the surface of the smart mirror. Due to the effect of gravity, the mud and dirt are deposited in the water droplets to the bottom of the water droplets. The water stains formed after the water droplets are dried have a color distribution related to the content of mud and dirt at that location.

[0099] Furthermore, the method of using a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image includes:

[0100] Detecting a target image from a grayscale image using a region growing algorithm, wherein the grayscale values ​​corresponding to the target image are all greater than or equal to the grayscale threshold;

[0101] If the target image exists, the target area of ​​the target image is obtained, and if the target area is greater than or equal to a preset grayscale area threshold, it is confirmed that the grayscale image corresponding to the target image is a stain image.

[0102] It is understandable that when there is a target image in the detection image, it is necessary to perform a cleaning operation on the identification detection area corresponding to the detection image. The region growing algorithm is a prior art and will not be described here. However, when graying the image, the gray value at the noise point may change due to the noise point in the image. Therefore, by comparing the target area and the gray area threshold, the situation of misjudging the stain image due to the interference of noise points can be eliminated, thereby solving the problem of waste of resources when cleaning the smart mirror. The target area is the area of ​​the target image.

[0103] It should be explained that the step of using the one or more first cleaning areas to fit one or more cleaning schemes includes:

[0104] Sequentially extracting first cleaning regions from the one or more first cleaning regions, and performing the following operations on the extracted first cleaning regions:

[0105] The second search area is obtained by using the extracted first cleaning area, wherein the second search area is a first cleaning area adjacent to the extracted first cleaning area, and the extracted first cleaning area is eliminated from one or more first cleaning areas, and the second search area is used as the extracted first cleaning area, and the step of obtaining the second search area by using the extracted first cleaning area is returned to until the second search area cannot be obtained by using the extracted first cleaning area, and one or more initial cleaning areas are obtained;

[0106] Sequentially extracting initial cleaning regions from the one or more initial cleaning regions, and performing the following operations on the extracted initial cleaning regions:

[0107] One or more cleaning solutions are obtained based on the extracted initial cleaning area, wherein the one or more cleaning solutions are as follows:

[0108] Cleaning solution 1: performing a cleaning operation on each first cleaning area in the extracted initial cleaning area;

[0109] Cleaning scheme 2: obtaining one or more second cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more second cleaning schemes includes: one or more second cleaning areas, and the second cleaning scheme is composed of the second cleaning area and R first cleaning areas, wherein R is an integer greater than or equal to 0, and the area corresponding to the second cleaning area in the one or more second cleaning areas is greater than the area threshold;

[0110] Cleaning scheme three: obtaining one or more third cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more third cleaning schemes includes: one or more third cleaning areas, and the third cleaning scheme is composed of Q first cleaning areas, P second cleaning areas, and a third cleaning area, wherein Q and P are both integers greater than or equal to 0, and the third cleaning area in the one or more third cleaning areas includes the detection area corresponding to the detection image except the first cleaning area;

[0111] The one or more cleaning schemes are composed of cleaning scheme one, one or more second cleaning schemes corresponding to cleaning scheme two, and one or more third cleaning schemes corresponding to cleaning scheme three.

[0112] It should be explained that the purpose of using the first cleaning area to obtain one or more initial cleaning areas is to obtain all areas adjacent to the extracted first cleaning area, that is, the initial cleaning area. In some cases, the energy consumption required for cleaning the initial cleaning area will be less than the energy consumption of performing cleaning operations on each first cleaning area in the initial cleaning area. The purpose of formulating three cleaning schemes through the initial cleaning area is to fit possible cleaning schemes and obtain the cleaning scheme with the least energy consumption through the three possible cleaning schemes, thereby solving the problem of resource waste caused by the smart mirror performing cleaning operations. Optionally, the empirical method is used to obtain cleaning scheme two and cleaning scheme three, and other technologies can achieve the same effect, which will not be repeated here.

[0113] Exemplarily, the smart mirror is composed of 9 identification detection areas, and there are multiple first cleaning areas in the smart mirror, wherein the multiple first cleaning areas include: (1, 1), (1, 2), (1, 3), (3, 1), (3, 2) and (3, 3). Two initial cleaning areas can be fitted using the multiple first cleaning areas, wherein the first initial cleaning area is composed of identification detection areas corresponding to (1, 1), (1, 2) and (1, 3), and the second initial cleaning area is composed of identification detection areas corresponding to (3, 1), (3, 2) and (3, 3). In this case, cleaning plan 2 saves energy consumption of the mobile cleaning mechanism compared to cleaning plan 1, and can achieve the same cleaning effect. Therefore, cleaning plan 2 is better than cleaning plan 1. If the multiple first cleaning areas in the smart mirror include: (1, 1), (1, 2), (1, 3), (2, 1), (2, 2), (3, 1), (3, 2) and (3, 3), then the possible cleaning solution three is: perform cleaning operations on all areas corresponding to the smart mirror, then the possible cleaning solution two is: composed of a second cleaning area and two first cleaning areas, wherein the second cleaning area is composed of: (1, 1), (1, 2), (2, 1), (2, 2), (3, 1) and (3, 2) corresponding to the identification detection area, the two first cleaning areas include: the first first cleaning area is composed of the identification detection area corresponding to (1, 3), and the second first cleaning area is composed of the identification detection area corresponding to (3, 3). In this case, it is necessary to screen the possible cleaning solutions and select the cleaning solution with the minimum total energy consumption as the target cleaning solution. For specific screening implementation methods, please refer to the subsequent embodiments.

[0114] S3. Obtain a target cleaning scheme according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme requiring the least energy consumption.

[0115] It should be explained that the step of obtaining a target cleaning scheme according to the one or more cleaning schemes includes:

[0116] Extract cleaning schemes from the one or more cleaning schemes in sequence, and perform the following operations on the extracted cleaning schemes:

[0117] The energy consumption evaluation value is calculated using the pre-built energy consumption evaluation relationship and the extracted cleaning plan, where the energy consumption evaluation relationship is as follows:

[0118]

[0119] Among them, Z represents the energy consumption evaluation value during cleaning, n represents a total of n target cleaning areas, x i It means that there are x target cleaning areas of type i, f iThe expression relationship for the total energy consumption required when cleaning the i-th target cleaning area is expressed as follows: i represents the energy consumption of the cleaning unit when cleaning the i-th target cleaning area, v i represents the energy consumption of the cleaning unit when cleaning the i-th target cleaning area, a i represents the energy consumption of the drying unit when cleaning the i-th target cleaning area, b i represents the energy consumption required by the detergent spraying unit when cleaning the i-th target cleaning area, y represents the energy consumption required by the mobile cleaning mechanism when cleaning, and the target cleaning area is composed of one or more first cleaning areas, one or more second cleaning areas, and one or more third cleaning areas;

[0120] The energy consumption evaluation values ​​are summarized to obtain an energy consumption evaluation value set, and a target cleaning solution is obtained based on the energy consumption evaluation value set.

[0121] It can be understood that the target cleaning scheme is the cleaning scheme corresponding to the minimum energy consumption evaluation value in the energy consumption evaluation value set.

[0122] Furthermore, the energy consumption required by the mobile cleaning mechanism is obtained, including:

[0123] Extract cleaning schemes from the one or more cleaning schemes in sequence, and perform the following operations on the extracted cleaning schemes:

[0124] Performing a particle point operation on one or more target cleaning areas in the extracted cleaning scheme to obtain one or more path points, wherein the one or more path points correspond to the one or more target cleaning areas one by one;

[0125] A target path is obtained using a pre-built path planning algorithm and the one or more path points, and energy consumption required by the mobile cleaning mechanism is obtained based on the target path.

[0126] It should be explained that the particle operation is: regardless of the volume of the rectangle corresponding to one or more target cleaning areas, the center of the rectangle is used to represent the position of the target cleaning area. Optionally, the path planning algorithm is an ant colony algorithm, and other technologies can achieve the same effect, which will not be repeated here. The energy consumption required for the mobile cleaning mechanism is obtained based on the target path, and the energy consumption required for the mobile unit distance is obtained, and the energy consumption is multiplied by the distance corresponding to the target path to obtain the energy consumption required for the mobile cleaning mechanism. Optionally, an orthogonal experiment is used to obtain the expression relationship of the total energy consumption required in the energy consumption evaluation relationship, that is, according to different types of target cleaning areas, an expression relationship for expressing the energy consumption corresponding to each target cleaning area is fitted. The type of target cleaning area is related to the shape and area of ​​the target cleaning area. For example: the enclosed target cleaning areas are all rectangular areas with an area of ​​2, but the expression relationship of the energy consumption corresponding to the 1×2 rectangular area may be different from the expression relationship of the energy consumption corresponding to the 2×1 rectangular area.

[0127] S4. Perform a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning solution to obtain an initially cleaned smart mirror.

[0128] It should be explained that the use of the cleaning mechanism and the target cleaning scheme to perform a cleaning operation on the smart mirror to obtain an initially cleaned smart mirror includes:

[0129] Extracting target cleaning areas from the target cleaning scheme in sequence, and performing the following operations on the extracted target cleaning areas;

[0130] Using the cleaning unit to perform a wetting operation on the extracted target cleaning area to obtain a wet area, wherein the execution time of the wetting operation is preset, using the cleaning agent spraying unit to spray a pre-constructed cleaning agent on the wet area to obtain a first cleaning area, and based on the cleaning unit performing a cleaning operation on the first cleaning area to obtain a second cleaning area;

[0131] A third cleaning area is obtained based on the second cleaning area, the cleaning unit, the cleaning unit, the waste liquid guiding unit and the waste liquid collecting unit, and the drying unit is used to perform a drying operation on the third cleaning area to obtain an initially cleaned smart mirror.

[0132] It should be explained that the wetting operation refers to the use of a cleaning unit to spray liquid in the target cleaning area to wet the target cleaning area. The purpose is to remove easily removable contaminants on the surface of the target cleaning area as much as possible, so that the detergent sprayed by the detergent spraying unit can better contact and react with the contaminants that are not easy to remove. The wet area is the target cleaning area after the cleaning unit continuously sprays the pre-constructed liquid into the target cleaning area during the execution time. The purpose of obtaining the third cleaning area based on the second cleaning area, the cleaning unit, the cleaning unit, the waste liquid guiding unit and the waste liquid collecting unit is to remove the residual detergent in the target cleaning area.

[0133] It is understandable that the target cleaning area may include relatively stubborn stains, and therefore, performing only one cleaning operation on the target cleaning area may not be able to remove the stubborn stains.

[0134] Exemplarily, the liquid sprayed by the cleaning unit is water, the cleaning agent pre-constructed in the cleaning agent spraying unit is detergent, the cleaning unit is a scraper, the execution time of the preset wet operation is 3s, the drying unit is a hot air fan output by the duct, the cleaning unit is used to continuously spray water mist to the target cleaning area within 3s, the target cleaning area after spraying the water mist is the wet area, the cleaning agent spraying unit is used to spray detergent into the wet area, the wet area after spraying the detergent is the first cleaning area, the scraper is used to scrape off the stains dissolved in the detergent in the first cleaning area to obtain the second cleaning area, the cleaning unit is used to spray water again in the second cleaning area, and the scraper is used to scrape off the water mist sprayed twice in the second cleaning area, and the waste liquid guide unit and the waste liquid collection unit are used to collect the waste liquid generated during the cleaning process to obtain the third cleaning area. The purpose of using the drying unit to perform a drying operation on the third cleaning area is to eliminate the liquid in the third cleaning area to improve the accuracy of judging the cleaning condition of the smart mirror. For example, there is some residual liquid in the third cleaning area, and the contaminants in the liquid cannot be detected by the region growing algorithm.

[0135] S5. After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror, and the cleaning report is sent to an initiator of the cleaning instruction to clean the smart mirror.

[0136] Further, the confirming that the initially cleaned smart mirror is a target cleaned smart mirror includes:

[0137] Acquire a second stain image set based on the initial cleaning smart mirror, wherein the second stain image set includes one or more second stain images, and acquire one or more marked cleaning areas based on the second stain image set, wherein the one or more second stain images correspond one-to-one to the one or more marked cleaning areas;

[0138] The initially cleaned smart mirror is identified as a target cleaned smart mirror based on the one or more identified cleaning areas.

[0139] It should be explained that the second stain image is an image of the stains included in the initially cleaned smart mirror, that is, an image in which only one cleaning operation is performed on the target cleaning area, and stubborn stains cannot be removed. The second stain image set is acquired in the same manner as the stain image set, and can achieve the same effect, which will not be repeated here. The marked cleaning area is the marked detection area corresponding to the second stain image. For example: a cleaning operation is performed on a 3×3 smart mirror, and there are still unremoved stains in the areas corresponding to (2, 2) and (3, 3) in the cleaned smart mirror, that is, the initially cleaned smart mirror, then the areas corresponding to (2, 2) and (3, 3) are both marked cleaning areas.

[0140] It should be understood that the step of confirming the initially cleaned smart mirror as a target cleaned smart mirror based on the one or more identified cleaning areas includes:

[0141] The one or more marked cleaning areas are used as one or more first cleaning areas, and a drying detection image set is acquired using a pre-built cycle experiment, a drying unit, and one or more first cleaning areas, wherein the number of executions of the cycle experiment is preset, and the cycle experiment is: returning to the step of acquiring one or more first cleaning areas based on the stain image set, the drying detection image set includes one or more drying detection images, and the one or more drying detection images correspond to the one or more first cleaning areas one by one;

[0142] Extracting drying detection images from the drying detection image set in sequence, and performing the following operations on the extracted drying detection images:

[0143] If the extracted drying detection image is not the second stain image or the cumulative number of executions of the cycle experiment is the number of executions, then the initially cleaned smart mirror is confirmed to be the target cleaned smart mirror.

[0144] Furthermore, the drying detection image set and the stain image set are acquired in the same manner and can achieve the same effects, which will not be described in detail herein.

[0145] It should be explained that there may be non-stains or stains that cannot be removed on the mirror surface of the smart mirror, for example: there are scratches on the mirror surface of the smart mirror, and the area where the scratches are located may be identified as an area where stains exist. Therefore, after the cumulative number of executions of the proposed cycle experiment is the number of executions, the initial cleaning smart mirror is confirmed to be the target cleaning smart mirror, and its purpose is to eliminate accidental factors and solve the problem of excessive energy consumption when cleaning the smart mirror. The cleaning report includes: after the cumulative number of executions of the cycle experiment is the number of executions, the dry detection image is still the second stain image, and the area corresponding to the dry detection image. For example: there are scratches on the mirror surface of the smart mirror in the area (2, 2), and there are also stains at the scratches, and the scratches will also be identified as stains. The preset number of executions is 3 times. During the second cleaning, the stains at the scratches are cleaned. Since the scratches will also be identified as stains, the third cleaning is performed on the area. After the third cleaning is performed, the cumulative number of executions of the cycle experiment is the execution number, then the cycle is terminated and a cleaning report is fed back, wherein the cleaning report is: there is stain in the area (2, 2).

[0146] Compared with the problems described in the background technology, the present invention first receives a cleaning instruction, and confirms a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a detergent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area. It can be seen that the present invention proposes an environment for cleaning the smart mirror when considering the cleaning of the smart mirror. The proposed cleaning mechanism can achieve directional cleaning of the smart mirror, and will not affect other areas that do not need to be cleaned during cleaning. Based on the smart mirror, one or more first cleaning areas are obtained, one or more cleaning schemes are fitted using the one or more first cleaning areas, and a target cleaning scheme is obtained according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme requiring the minimum energy consumption. It can be seen that the present invention first divides the smart mirror into a plurality of independently cleanable units, and can combine a plurality of independently cleanable units, thereby improving the feasibility of the present invention. Secondly, the present invention obtains a cleaning scheme requiring the minimum energy consumption from one or more cleaning schemes, and before formulating a cleaning scheme, uses image processing technology to perform recognition operations on the smart mirror, thereby identifying where the smart mirror needs to perform a cleaning operation as planned, thereby achieving directional cleaning of the smart mirror, and further solving the problem of high energy consumption required when cleaning the smart mirror. The cleaning mechanism and the target cleaning scheme are used to perform a cleaning operation on the smart mirror to obtain an initially cleaned smart mirror. After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror. It can be seen that the present invention, when cleaning the smart mirror, also considers that the stains to be cleaned may require multiple cleanings to remove, or that there may be special circumstances on the mirror surface of the smart mirror, which may result in the inability to remove the stains identified therein, and generates a cleaning report to improve the feasibility of the present invention. Therefore, the main purpose of the smart mirror cleaning method, device, electronic device and computer-readable storage medium of the Internet of Things proposed by the present invention is to solve the problems of high limitations and high energy consumption when cleaning the mirror surface of the smart mirror.

[0147] Embodiment 2:

[0148] like Figure 2 , which is a functional module diagram of an intelligent mirror cleaning device of the Internet of Things provided by an embodiment of the present invention.

[0149] The intelligent mirror cleaning device 100 of the Internet of Things of the present invention can be installed in an electronic device. The electronic device can be a smart mirror or a control device connected to the smart mirror in communication, such as a user's smart phone. According to the functions implemented, the intelligent mirror cleaning device 100 of the Internet of Things can include an instruction receiving and environment confirmation module 101, a cleaning scheme acquisition module 102, a target cleaning scheme confirmation module 103 and a target cleaning scheme execution and feedback module 104. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0150] The instruction receiving and environment confirmation module 101 is used to receive a cleaning instruction and confirm a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a detergent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area;

[0151] The cleaning scheme acquisition module 102 is used to acquire one or more first cleaning areas based on the smart mirror, wherein acquiring one or more first cleaning areas based on the smart mirror includes:

[0152] Performing a region division operation on the smart mirror based on a pre-built division model to obtain a plurality of initial detection regions, wherein an area corresponding to each initial detection region is equal to an area threshold corresponding to the division model, and the shape corresponding to the division model is preset to be a rectangle, wherein the division model is related to a target cleaning region that can be formed by a cleaning mechanism into one or more rectangles;

[0153] Sequentially extracting initial detection areas from the multiple initial detection areas, and performing the following operations on the extracted initial detection areas:

[0154] Performing a marking operation on the extracted initial detection area to obtain a marked detection area, and summarizing the marked detection area to obtain a marked detection area set;

[0155] Extracting the marker detection areas from the marker detection area set in sequence, and performing the following operations on the extracted marker detection areas:

[0156] Acquire a detection image based on the extracted identification detection area, perform a grayscale operation on the detection image to obtain a grayscale image, obtain a grayscale threshold for segmentation, and use a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image, wherein the grayscale value required by the region growing algorithm is preset as the grayscale threshold;

[0157] Summarizing the stain images to obtain a stain image set, and acquiring one or more first clean areas based on the stain image set, wherein the stain image set includes one or more stain images, and the one or more first clean areas correspond to the one or more stain images in a one-to-one manner;

[0158] Fitting one or more cleaning schemes using the one or more first cleaning areas comprises: extracting one of the first cleaning areas in turn from the one or more first cleaning areas, and performing the following operations on the extracted first cleaning areas: obtaining a second search area using the extracted first cleaning area, wherein the second search area is a first cleaning area adjacent to the extracted first cleaning area, and excluding the extracted first cleaning area from one or more first cleaning areas, and taking the second search area as the extracted first cleaning area, returning to the step of obtaining the second search area using the extracted first cleaning area until the second search area cannot be obtained using the extracted first cleaning area, thereby obtaining one or more initial cleaning areas; extracting initial cleaning areas in turn from the one or more initial cleaning areas, and performing the following operations on the extracted initial cleaning areas: obtaining one or more cleaning schemes based on the extracted initial cleaning area, wherein the one or more cleaning schemes are as follows: Cleaning scheme 1: obtaining the second search area using the extracted first cleaning area Perform a cleaning operation on each first cleaning area in the extracted initial cleaning area; Cleaning scheme two: obtain one or more second cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more second cleaning schemes includes: one or more second cleaning areas, and the second cleaning scheme is composed of the second cleaning area and R first cleaning areas, wherein R is an integer greater than or equal to 0, and the area corresponding to the second cleaning area in the one or more second cleaning areas is greater than the area threshold; Cleaning scheme three: obtain one or more third cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more third cleaning schemes includes: one or more third cleaning areas, and the third cleaning area is composed of Q first cleaning areas and P second cleaning areas and a third cleaning area, wherein Q and P are both integers greater than or equal to 0, and the third cleaning area in the one or more third cleaning areas includes the detection area corresponding to the detection image except the first cleaning area;

[0159] The one or more cleaning schemes are composed of cleaning scheme one, one or more second cleaning schemes corresponding to cleaning scheme two, and one or more third cleaning schemes corresponding to cleaning scheme three;

[0160] The target cleaning scheme confirmation module 103 is used to obtain a target cleaning scheme according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme that requires the least energy consumption;

[0161] The target cleaning scheme execution and feedback module 104 is used to perform a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initially cleaned smart mirror;

[0162] After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror, and the cleaning report is sent to an initiator of a cleaning instruction to achieve cleaning of the smart mirror.

[0163] In detail, each module in the intelligent mirror cleaning device 100 of the Internet of Things in the embodiment of the present invention is used in the same manner as described above. Figure 1 The same technical means are used as the intelligent mirror cleaning method of the Internet of Things described in, and can produce the same technical effects, so I will not go into details here.

[0164] Embodiment 3:

[0165] like Figure 3 , is a schematic diagram of the structure of an electronic device for implementing an intelligent mirror cleaning method of the Internet of Things provided by an embodiment of the present invention.

[0166] The electronic device 1 may include a processor 10, a memory 11, a bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as an intelligent mirror cleaning program of the Internet of Things.

[0167] Wherein, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. The memory 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a mobile hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), etc. equipped on the electronic device 1. Further, the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the smart mirror cleaning program of the Internet of Things, but also be used to temporarily store data that has been output or is to be output.

[0168] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (such as the smart mirror cleaning program of the Internet of Things, etc.), and calls the data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0169] The bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0170] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0171] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0172] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0173] Optionally, the electronic device 1 may further include a user interface, which may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device, etc. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0174] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0175] The smart mirror cleaning program of the Internet of Things stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0176] Receiving a cleaning instruction, and confirming a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a cleaning agent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit, and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area;

[0177] Acquiring one or more first cleaning areas based on the smart mirror, wherein acquiring one or more first cleaning areas based on the smart mirror comprises:

[0178] Performing a region division operation on the smart mirror based on a pre-built division model to obtain a plurality of initial detection regions, wherein an area corresponding to each initial detection region is equal to an area threshold corresponding to the division model, and the shape corresponding to the division model is preset to be a rectangle, wherein the division model is related to a target cleaning region that can be formed by a cleaning mechanism into one or more rectangles;

[0179] Sequentially extracting initial detection areas from the multiple initial detection areas, and performing the following operations on the extracted initial detection areas:

[0180] Performing a marking operation on the extracted initial detection area to obtain a marked detection area, and summarizing the marked detection area to obtain a marked detection area set;

[0181] Extracting the marker detection areas from the marker detection area set in sequence, and performing the following operations on the extracted marker detection areas:

[0182] Acquire a detection image based on the extracted identification detection area, perform a grayscale operation on the detection image to obtain a grayscale image, obtain a grayscale threshold for segmentation, and use a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image, wherein the grayscale value required by the region growing algorithm is preset as the grayscale threshold;

[0183] Summarizing the stain images to obtain a stain image set, and acquiring one or more first clean areas based on the stain image set, wherein the stain image set includes one or more stain images, and the one or more first clean areas correspond to the one or more stain images in a one-to-one manner;

[0184] Using the one or more first cleaning regions to fit one or more cleaning schemes includes: sequentially extracting one of the one or more first cleaning regions, and performing the following operations on the extracted first cleaning region:

[0185] The second search area is obtained by using the extracted first cleaning area, wherein the second search area is a first cleaning area adjacent to the extracted first cleaning area, and the extracted first cleaning area is eliminated from one or more first cleaning areas, and the second search area is used as the extracted first cleaning area, and the step of obtaining the second search area by using the extracted first cleaning area is returned to until the second search area cannot be obtained by using the extracted first cleaning area, and one or more initial cleaning areas are obtained;

[0186] Sequentially extracting initial cleaning regions from the one or more initial cleaning regions, and performing the following operations on the extracted initial cleaning regions:

[0187] One or more cleaning solutions are obtained based on the extracted initial cleaning area, wherein the one or more cleaning solutions are as follows:

[0188] Cleaning solution 1: performing a cleaning operation on each first cleaning area in the extracted initial cleaning area;

[0189] Cleaning scheme 2: obtaining one or more second cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more second cleaning schemes includes: one or more second cleaning areas, and the second cleaning scheme is composed of the second cleaning area and R first cleaning areas, wherein R is an integer greater than or equal to 0, and the area corresponding to the second cleaning area in the one or more second cleaning areas is greater than the area threshold;

[0190] Cleaning scheme three: obtaining one or more third cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more third cleaning schemes includes: one or more third cleaning areas, and the third cleaning scheme is composed of Q first cleaning areas, P second cleaning areas, and a third cleaning area, wherein Q and P are both integers greater than or equal to 0, and the third cleaning area in the one or more third cleaning areas includes the detection area corresponding to the detection image except the first cleaning area;

[0191] The one or more cleaning schemes are composed of cleaning scheme one, one or more second cleaning schemes corresponding to cleaning scheme two, and one or more third cleaning schemes corresponding to cleaning scheme three;

[0192] Obtaining a target cleaning scheme according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme requiring the least energy consumption;

[0193] Performing a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initially cleaned smart mirror;

[0194] After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror, and the cleaning report is sent to an initiator of a cleaning instruction to achieve cleaning of the smart mirror.

[0195] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figure 1 to Figure 2 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0196] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0197] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0198] Receiving a cleaning instruction, and confirming a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a cleaning agent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit, and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area;

[0199] Acquiring one or more first cleaning areas based on the smart mirror, wherein acquiring one or more first cleaning areas based on the smart mirror comprises:

[0200] Performing a region division operation on the smart mirror based on a pre-built division model to obtain a plurality of initial detection regions, wherein an area corresponding to each initial detection region is equal to an area threshold corresponding to the division model, and the shape corresponding to the division model is preset to be a rectangle, wherein the division model is related to a target cleaning region that can be formed by a cleaning mechanism into one or more rectangles;

[0201] Sequentially extracting initial detection areas from the multiple initial detection areas, and performing the following operations on the extracted initial detection areas:

[0202] Performing a marking operation on the extracted initial detection area to obtain a marked detection area, and summarizing the marked detection area to obtain a marked detection area set;

[0203] Extracting the marker detection areas from the marker detection area set in sequence, and performing the following operations on the extracted marker detection areas:

[0204] Acquire a detection image based on the extracted identification detection area, perform a grayscale operation on the detection image to obtain a grayscale image, obtain a grayscale threshold for segmentation, and use a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image, wherein the grayscale value required by the region growing algorithm is preset as the grayscale threshold;

[0205] Summarizing the stain images to obtain a stain image set, and acquiring one or more first clean areas based on the stain image set, wherein the stain image set includes one or more stain images, and the one or more first clean areas correspond to the one or more stain images in a one-to-one manner;

[0206] Using the one or more first cleaning regions to fit one or more cleaning schemes includes: sequentially extracting one of the one or more first cleaning regions, and performing the following operations on the extracted first cleaning region:

[0207] The second search area is obtained by using the extracted first cleaning area, wherein the second search area is a first cleaning area adjacent to the extracted first cleaning area, and the extracted first cleaning area is eliminated from one or more first cleaning areas, and the second search area is used as the extracted first cleaning area, and the step of obtaining the second search area by using the extracted first cleaning area is returned to until the second search area cannot be obtained by using the extracted first cleaning area, and one or more initial cleaning areas are obtained;

[0208] Sequentially extracting initial cleaning regions from the one or more initial cleaning regions, and performing the following operations on the extracted initial cleaning regions:

[0209] One or more cleaning solutions are obtained based on the extracted initial cleaning area, wherein the one or more cleaning solutions are as follows:

[0210] Cleaning solution 1: performing a cleaning operation on each first cleaning area in the extracted initial cleaning area;

[0211] Cleaning scheme 2: obtaining one or more second cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more second cleaning schemes includes: one or more second cleaning areas, and the second cleaning scheme is composed of the second cleaning area and R first cleaning areas, wherein R is an integer greater than or equal to 0, and the area corresponding to the second cleaning area in the one or more second cleaning areas is greater than the area threshold;

[0212] Cleaning scheme three: obtaining one or more third cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more third cleaning schemes includes: one or more third cleaning areas, and the third cleaning scheme is composed of Q first cleaning areas, P second cleaning areas, and a third cleaning area, wherein Q and P are both integers greater than or equal to 0, and the third cleaning area in the one or more third cleaning areas includes the detection area corresponding to the detection image except the first cleaning area;

[0213] The one or more cleaning schemes are composed of cleaning scheme one, one or more second cleaning schemes corresponding to cleaning scheme two, and one or more third cleaning schemes corresponding to cleaning scheme three;

[0214] Obtaining a target cleaning scheme according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme requiring the least energy consumption;

[0215] Performing a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initially cleaned smart mirror;

[0216] After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror, and the cleaning report is sent to an initiator of a cleaning instruction to achieve cleaning of the smart mirror.

[0217] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0218] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0219] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0220] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An intelligent mirror cleaning method for the Internet of Things, characterized in that: The method comprises: Receiving a cleaning instruction, and confirming a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a cleaning agent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit, and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area; Acquiring one or more first cleaning areas based on the smart mirror, wherein acquiring one or more first cleaning areas based on the smart mirror comprises: Performing a region division operation on the smart mirror based on a pre-built division model to obtain a plurality of initial detection regions, wherein an area corresponding to each initial detection region is equal to an area threshold corresponding to the division model, and the shape corresponding to the division model is preset to be a rectangle, wherein the division model is related to a target cleaning region that can be formed by a cleaning mechanism into one or more rectangles; Sequentially extracting initial detection areas from the multiple initial detection areas, and performing the following operations on the extracted initial detection areas: Performing a marking operation on the extracted initial detection area to obtain a marked detection area, and summarizing the marked detection area to obtain a marked detection area set; Extracting the marker detection areas from the marker detection area set in sequence, and performing the following operations on the extracted marker detection areas: Acquire a detection image based on the extracted identification detection area, perform a grayscale operation on the detection image to obtain a grayscale image, obtain a grayscale threshold for segmentation, and use a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image, wherein the grayscale value required by the region growing algorithm is preset as the grayscale threshold; Summarizing the stain images to obtain a stain image set, and acquiring one or more first clean areas based on the stain image set, wherein the stain image set includes one or more stain images, and the one or more first clean areas correspond to the one or more stain images in a one-to-one manner; Using the one or more first cleaning regions to fit one or more cleaning schemes includes: sequentially extracting one of the one or more first cleaning regions, and performing the following operations on the extracted first cleaning region: The second search area is obtained by using the extracted first cleaning area, wherein the second search area is a first cleaning area adjacent to the extracted first cleaning area, and the extracted first cleaning area is eliminated from one or more first cleaning areas, and the second search area is used as the extracted first cleaning area, and the step of obtaining the second search area by using the extracted first cleaning area is returned to until the second search area cannot be obtained by using the extracted first cleaning area, and one or more initial cleaning areas are obtained; Sequentially extracting initial cleaning regions from the one or more initial cleaning regions, and performing the following operations on the extracted initial cleaning regions: One or more cleaning solutions are obtained based on the extracted initial cleaning area, wherein the one or more cleaning solutions are as follows: Cleaning solution 1: performing a cleaning operation on each first cleaning area in the extracted initial cleaning area; Cleaning scheme 2: obtaining one or more second cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more second cleaning schemes includes: one or more second cleaning areas, and the second cleaning scheme is composed of the second cleaning area and R first cleaning areas, wherein R is an integer greater than or equal to 0, and the area corresponding to the second cleaning area in the one or more second cleaning areas is greater than the area threshold; Cleaning scheme three: obtaining one or more third cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more third cleaning schemes includes: one or more third cleaning areas, and the third cleaning scheme is composed of Q first cleaning areas, P second cleaning areas, and a third cleaning area, wherein Q and P are both integers greater than or equal to 0, and the third cleaning area in the one or more third cleaning areas includes the detection area corresponding to the detection image except the first cleaning area; The one or more cleaning schemes are composed of cleaning scheme one, one or more second cleaning schemes corresponding to cleaning scheme two, and one or more third cleaning schemes corresponding to cleaning scheme three; Obtaining a target cleaning scheme according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme requiring the least energy consumption; Performing a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initially cleaned smart mirror; After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror, and the cleaning report is sent to an initiator of a cleaning instruction to achieve cleaning of the smart mirror.

2. The intelligent mirror cleaning method of the Internet of Things according to claim 1, characterized in that: The method of using a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image includes: Detecting a target image from a grayscale image using a region growing algorithm, wherein the grayscale values ​​corresponding to the target image are all greater than or equal to the grayscale threshold; If the target image exists, the target area of ​​the target image is obtained, and if the target area is greater than or equal to a preset grayscale area threshold, it is confirmed that the grayscale image corresponding to the target image is a stain image.

3. The intelligent mirror cleaning method of the Internet of Things as claimed in claim 2, characterized in that: The step of obtaining a grayscale threshold for segmentation includes: A reference image set is obtained as a reference, wherein the reference image set includes a plurality of reference images, reference images are extracted from the reference image set in sequence, and the following operations are performed on the extracted reference images: A grayscale operation is performed on the extracted reference image to obtain a grayscale reference image, the grayscale reference images are summarized to obtain a grayscale reference image set, and the grayscale threshold is calculated using a pre-constructed grayscale threshold relationship and the grayscale reference image set, wherein the grayscale threshold relationship is as follows: Among them, G represents the grayscale threshold, represents the parameters of the kth grayscale reference image in the grayscale reference image set during calculation, e j represents the grayscale value of the jth pixel in the kth grayscale reference image of the grayscale reference image set, D represents the total number of D grayscale values ​​in the kth grayscale reference image of the grayscale reference image set, and p k represents the coefficient of the preset k-th grayscale reference image, F represents that there are F grayscale reference images in the grayscale reference image set, and 4. The intelligent mirror cleaning method of the Internet of Things as claimed in claim 3, characterized in that: The step of obtaining a target cleaning scheme according to the one or more cleaning schemes comprises: Extract cleaning schemes from the one or more cleaning schemes in sequence, and perform the following operations on the extracted cleaning schemes: The energy consumption evaluation value is calculated using the pre-built energy consumption evaluation relationship and the extracted cleaning plan, where the energy consumption evaluation relationship is as follows: Among them, Z represents the energy consumption evaluation value during cleaning, n represents a total of n target cleaning areas, x i It means that there are x target cleaning areas of type i, f i The expression relationship for the total energy consumption required when cleaning the i-th target cleaning area is expressed as follows: i represents the energy consumption of the cleaning unit when cleaning the i-th target cleaning area, v i represents the energy consumption of the cleaning unit when cleaning the i-th target cleaning area, a i represents the energy consumption of the drying unit when cleaning the i-th target cleaning area, b i represents the energy consumption required by the detergent spraying unit when cleaning the i-th target cleaning area, y represents the energy consumption required by the mobile cleaning mechanism when cleaning, and the target cleaning area is composed of one or more first cleaning areas, one or more second cleaning areas, and one or more third cleaning areas; The energy consumption evaluation values ​​are summarized to obtain an energy consumption evaluation value set, and a target cleaning solution is obtained based on the energy consumption evaluation value set.

5. The intelligent mirror cleaning method of the Internet of Things as claimed in claim 4, characterized in that: The method of performing a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initially cleaned smart mirror includes: Extracting target cleaning areas from the target cleaning scheme in sequence, and performing the following operations on the extracted target cleaning areas; Using the cleaning unit to perform a wetting operation on the extracted target cleaning area to obtain a wet area, wherein the execution time of the wetting operation is preset, using the cleaning agent spraying unit to spray a pre-constructed cleaning agent on the wet area to obtain a first cleaning area, and based on the cleaning unit performing a cleaning operation on the first cleaning area to obtain a second cleaning area; A third cleaning area is obtained based on the second cleaning area, the cleaning unit, the cleaning unit, the waste liquid guiding unit and the waste liquid collecting unit, and the drying unit is used to perform a drying operation on the third cleaning area to obtain an initially cleaned smart mirror.

6. The intelligent mirror cleaning method of the Internet of Things as claimed in claim 5, characterized in that: The confirming that the initially cleaned smart mirror is a target cleaned smart mirror comprises: Acquire a second stain image set based on the initial cleaning smart mirror, wherein the second stain image set includes one or more second stain images, and acquire one or more marked cleaning areas based on the second stain image set, wherein the one or more second stain images correspond one-to-one to the one or more marked cleaning areas; The initially cleaned smart mirror is identified as a target cleaned smart mirror based on the one or more identified cleaning areas.

7. The intelligent mirror cleaning method of the Internet of Things according to claim 6, characterized in that: The step of confirming the initially cleaned smart mirror as a target cleaned smart mirror based on the one or more identified cleaning areas includes: The one or more marked cleaning areas are used as one or more first cleaning areas, and a drying detection image set is acquired using a pre-built cycle experiment, a drying unit, and one or more first cleaning areas, wherein the number of executions of the cycle experiment is preset, and the cycle experiment is: returning to the step of acquiring one or more first cleaning areas based on the stain image set, the drying detection image set includes one or more drying detection images, and the one or more drying detection images correspond to the one or more first cleaning areas one by one; Extracting drying detection images from the drying detection image set in sequence, and performing the following operations on the extracted drying detection images: If the extracted drying detection image is not the second stain image or the cumulative number of executions of the cycle experiment is the number of executions, then the initially cleaned smart mirror is confirmed to be the target cleaned smart mirror.

8. An intelligent mirror cleaning device for the Internet of Things, characterized in that: The device comprises: An instruction receiving and environment confirmation module, used for receiving a cleaning instruction and confirming a cleaning environment based on the cleaning instruction, wherein the cleaning environment includes: a smart mirror to be cleaned and a cleaning mechanism, wherein the cleaning mechanism is composed of: a detection unit, a detergent spraying unit, a cleaning unit, a washing unit, a drying unit, a waste liquid guiding unit and a waste liquid collecting unit, and the cleaning mechanism will form one or more rectangular target cleaning areas according to the proposed cleaning area; A cleaning scheme acquisition module is used to acquire one or more first cleaning areas based on the smart mirror, wherein acquiring one or more first cleaning areas based on the smart mirror includes: Performing a region division operation on the smart mirror based on a pre-built division model to obtain a plurality of initial detection regions, wherein an area corresponding to each initial detection region is equal to an area threshold corresponding to the division model, and the shape corresponding to the division model is preset to be a rectangle, wherein the division model is related to a target cleaning region that can be formed by a cleaning mechanism into one or more rectangles; Sequentially extracting initial detection areas from the multiple initial detection areas, and performing the following operations on the extracted initial detection areas: Performing a marking operation on the extracted initial detection area to obtain a marked detection area, and summarizing the marked detection area to obtain a marked detection area set; Extracting the marker detection areas from the marker detection area set in sequence, and performing the following operations on the extracted marker detection areas: Acquire a detection image based on the extracted identification detection area, perform a grayscale operation on the detection image to obtain a grayscale image, obtain a grayscale threshold for segmentation, and use a pre-built region growing algorithm and a grayscale threshold to confirm that the grayscale image is a stain image, wherein the grayscale value required by the region growing algorithm is preset as the grayscale threshold; Summarizing the stain images to obtain a stain image set, and acquiring one or more first clean areas based on the stain image set, wherein the stain image set includes one or more stain images, and the one or more first clean areas correspond to the one or more stain images in a one-to-one manner; Fitting one or more cleaning schemes using the one or more first cleaning areas comprises: extracting one of the first cleaning areas in turn from the one or more first cleaning areas, and performing the following operations on the extracted first cleaning areas: obtaining a second search area using the extracted first cleaning area, wherein the second search area is a first cleaning area adjacent to the extracted first cleaning area, and excluding the extracted first cleaning area from one or more first cleaning areas, and taking the second search area as the extracted first cleaning area, returning to the step of obtaining the second search area using the extracted first cleaning area until the second search area cannot be obtained using the extracted first cleaning area, thereby obtaining one or more initial cleaning areas; extracting initial cleaning areas in turn from the one or more initial cleaning areas, and performing the following operations on the extracted initial cleaning areas: obtaining one or more cleaning schemes based on the extracted initial cleaning area, wherein the one or more cleaning schemes are as follows: Cleaning scheme 1: obtaining the second search area using the extracted first cleaning area Perform a cleaning operation on each first cleaning area in the extracted initial cleaning area; Cleaning scheme two: obtain one or more second cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more second cleaning schemes includes: one or more second cleaning areas, and the second cleaning scheme is composed of the second cleaning area and R first cleaning areas, wherein R is an integer greater than or equal to 0, and the area corresponding to the second cleaning area in the one or more second cleaning areas is greater than the area threshold; Cleaning scheme three: obtain one or more third cleaning schemes based on the extracted initial cleaning area, wherein each of the one or more third cleaning schemes includes: one or more third cleaning areas, and the third cleaning area is composed of Q first cleaning areas and P second cleaning areas and a third cleaning area, wherein Q and P are both integers greater than or equal to 0, and the third cleaning area in the one or more third cleaning areas includes the detection area corresponding to the detection image except the first cleaning area; The one or more cleaning schemes are composed of cleaning scheme one, one or more second cleaning schemes corresponding to cleaning scheme two, and one or more third cleaning schemes corresponding to cleaning scheme three; A target cleaning scheme confirmation module, used to obtain a target cleaning scheme according to the one or more cleaning schemes, wherein the target cleaning scheme is a cleaning scheme requiring the least energy consumption; A target cleaning scheme execution and feedback module, used to perform a cleaning operation on the smart mirror using the cleaning mechanism and the target cleaning scheme to obtain an initially cleaned smart mirror; After confirming that the initially cleaned smart mirror is a target cleaned smart mirror, a cleaning report is obtained based on the target cleaned smart mirror, and the cleaning report is sent to an initiator of a cleaning instruction to achieve cleaning of the smart mirror.

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