Pet-based cleaning method, cleaning system, electronic equipment and storage medium

Abstract

The invention provides a pet-based cleaning method and system, electronic equipment and a storage medium, and the method comprises the steps: determining a cleaning path aiming at an environment when a cleaning event aiming at the environment of the cleaning system is triggered; and guiding the pet to move according to the cleaning path so as to clean the environment. The pet is guided to move according to the determined cleaning path, and hair, soles and the like of the pet can be used for cleaning areas which cannot be cleaned by the cleaning system.

Description

Technical Field

[0001] This application belongs to the technical field of environmental cleaning, specifically relating to a pet-based cleaning method, cleaning system, electronic device, and storage medium. Background Technology

[0002] In related technologies, cleaning systems can clean environments (e.g., bedrooms) by moving around; however, they cannot effectively clean areas such as under sofas, under beds, furniture crevices, and cat trees. Summary of the Invention

[0003] In view of the above problems, pet-based cleaning methods, cleaning systems, electronic devices, and storage media are proposed to overcome or at least partially solve the above problems, including: A pet-based cleaning method, applied to a cleaning system, the method comprising: When a cleaning event is triggered in the environment targeted by the cleaning system, a cleaning path is determined for that environment; Guide the pet to move along the cleaning path to clean the environment.

[0004] In some embodiments, the method further includes: Data is collected from the pet to obtain target sensor data; Based on the target sensing data, determine the pet's emotional intention; When the emotional intent is an interactive intent, a cleaning event is determined that triggers the cleaning system for the environment in which it targets.

[0005] In some embodiments, the cleaning system includes at least one of the following sensors: Capacitive sensors, light field touch sensors, image acquisition sensors, and sound acquisition sensors; The target sensing data includes at least one of the following: Capacitance change data, light trajectory data, light intensity change data, image data, and audio data.

[0006] In some embodiments, the method further includes: Obtain pollution status information of the environment; Based on the pollution status information, determine whether to trigger a cleaning event for the environment targeted by the cleaning system.

[0007] In some embodiments, determining a cleaning path for the environment includes: Based on the pollution status information, determine the pollution level information of each area in the environment; The cleaning path is generated based on the pollution level information.

[0008] In some embodiments, guiding the pet to move along the cleaning path includes: Determine the target projection image; The target projection image is projected along the cleaning path.

[0009] In some embodiments, when projecting the target projection image along the cleaning path, the method further includes: Play target audio data corresponding to the target projected image at the current projection position of the target projected image; and / or, Airflow is directed to the current projection position of the target image.

[0010] This application also provides a cleaning system that applies the pet-based cleaning method described above, the cleaning system comprising: The target sensing module is used to collect sensing data on the environment targeted by the cleaning system. The control module is used to determine whether a cleaning event for the environment targeted by the cleaning system is triggered based on the sensor data; when a cleaning event for the environment targeted by the cleaning system is triggered, it determines a cleaning path for the environment; and guides the pet to move along the cleaning path to clean the environment. A guidance module is used to guide the pet to move along the cleaning path in order to clean the environment.

[0011] In some embodiments, the target sensing module includes at least one of the following: A capacitive sensor is used to sense changes in an electric field and output capacitance change data. A light field touch sensor includes a quantum dot fluorescent coating, a light source unit, and a light acquisition module; the light source unit is used to emit excitation light to the quantum dot fluorescent coating; the light acquisition module is used to acquire the excitation light received on the quantum dot fluorescent coating to obtain light trajectory data and / or light intensity change data; An image acquisition sensor is used to acquire images of the environment and output image data; A sound acquisition sensor is used to acquire sound from the environment and output audio data.

[0012] In some embodiments, the boot module includes: The projection unit is used to project a target image according to the cleaning path.

[0013] In some embodiments, the boot module further includes at least one of the following units: An audio playback unit is used to play target audio data corresponding to the target projection image at the current projection position of the target projection image; The airflow projection unit is used to directionally project airflow at the current projection position of the target projection image.

[0014] In some embodiments, the cleaning system further includes: An energy harvesting module is used to convert the pet's kinetic energy into electrical energy and supply it to the cleaning system.

[0015] This application also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the above-described pet-based cleaning method.

[0016] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described pet-based cleaning method.

[0017] The embodiments of this application have the following advantages: In this embodiment, when a cleaning event is triggered in the environment targeted by the cleaning system, a cleaning path is determined for that environment; the pet is then guided to move along the cleaning path to clean the environment. By guiding the pet to move along the determined cleaning path, this application can utilize the pet's fur, paws, etc., to clean areas that the cleaning system cannot reach. Attached Figure Description

[0018] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart illustrating the steps of a pet-based cleaning method according to an embodiment of this application; Figure 2 This is a flowchart illustrating the steps of another pet-based cleaning method according to an embodiment of this application; Figure 3 This is a flowchart illustrating the steps of another pet-based cleaning method according to an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a cleaning system according to an embodiment of this application; Figure 5 This is a schematic diagram illustrating the operation of the pet air purifier according to an embodiment of this application; Figure 6 This is a schematic diagram of a light field touch-AR collaborative excitation system according to an embodiment of this application; Figure 7This is a schematic diagram of the self-powered behavior response according to an embodiment of this application; Figure 8 This is a schematic diagram of the operation of the metaverse training extension platform according to an embodiment of this application. Detailed Implementation

[0019] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0020] To effectively clean areas such as under sofas, beds, furniture crevices, and cat trees, which are difficult to clean, this application provides a pet-based cleaning method that uses pets as "living cleaners." By guiding the pet along a predetermined cleaning path (e.g., under sofas, beds, furniture crevices, cat trees), the pet's fur and paws are used to clean areas that traditional cleaning systems cannot reach. For example, refer to... Figure 1 , Figure 1 A flowchart illustrating the steps of a pet-based cleaning method according to an embodiment of this application is shown.

[0021] like Figure 1 As shown, this pet-based cleaning method may include the following steps: Step 101: When a cleaning event is triggered in the environment targeted by the cleaning system, determine the cleaning path for that environment.

[0022] The cleaning system may include commercially available pet purification systems, pet air purifiers, etc., as well as robot vacuums, floor cleaning purifiers, robot vacuums and mops, etc. It may also include other smart devices, such as smart speakers, smart air conditioners, etc. This application embodiment does not limit this.

[0023] In some embodiments, the cleaning system may be deployed in an environment that the cleaning system can clean, such as a bedroom, living room, or the entire house.

[0024] During operation, the cleaning system can continuously detect whether a cleaning event is triggered in the environment it is targeting. For example, when a user triggers the cleaning system to clean the environment, the cleaning system can determine that a cleaning event has been triggered. Another example is when the environment is very dirty; yet another example is that since this application is based on pets to perform cleaning work, the presence of a pet can also trigger a cleaning event. This application does not impose any limitations on this aspect.

[0025] If no cleaning event is detected in the environment targeted by the cleaning system, the detection can continue to determine whether a cleaning event is triggered in the environment targeted by the cleaning system.

[0026] Conversely, if a cleaning event is detected that triggers the cleaning system in the environment it targets, a cleaning path can be determined for that environment. For example, cleaning paths can be designed to cover areas such as under sofas, under beds, furniture crevices, and cat trees, in order to clean areas that cannot be reached by conventional cleaning systems.

[0027] In another example, users can also set the cleaning path themselves; specifically, users can plan the cleaning path based on the objects placed in each area and their cleanliness level.

[0028] Step 102: Guide your pet to move along the cleaning path to clean the environment.

[0029] After determining the cleaning path, the cleaning system can guide the pet to move along the path. When the pet moves along the cleaning path and passes through the corresponding area, the pet's fur, paws, etc. will clean these areas, thereby absorbing pet hair, dander, dust and other dirt from these areas, thus completing the cleaning of these areas in the environment.

[0030] In this embodiment, when a cleaning event is triggered in the environment targeted by the cleaning system, a cleaning path is determined for that environment; the pet is then guided to move along the cleaning path to clean the environment. By guiding the pet to move along the determined cleaning path, this application can utilize the pet's fur, paws, etc., to clean areas that the cleaning system cannot reach.

[0031] Reference Figure 2 The diagram illustrates a flowchart of another pet-based cleaning method according to an embodiment of this application, which may include the following steps: Step 201: Collect data from the pet to obtain target sensor data.

[0032] In some embodiments, the determination of whether to trigger a cleaning event in the environment targeted by the cleaning system can be based on the pet's intention; for example, when the pet approaches the cleaning system, or when the pet has the intention to interact or play, it can be determined that a cleaning event in the environment targeted by the cleaning system is triggered.

[0033] In this application, the sensors can be used to collect data from the pet to obtain target sensing data.

[0034] In some embodiments of this application, the cleaning system may include at least one of the following sensors: a capacitive sensor, a light field touch sensor, an image acquisition sensor, and a sound acquisition sensor.

[0035] The capacitive sensor can be used to sense changes in the electric field. When a pet approaches, the electric field detected by the capacitive sensor changes, and the sensor outputs capacitance change data. In this application, when a user approaches and causes the capacitive sensor to output capacitance change data, a cleaning event for the environment targeted by the cleaning system can be triggered.

[0036] The light field touch sensor can include a quantum dot fluorescent coating, a light source unit, and a light acquisition module. The light source unit emits excitation light to the quantum dot fluorescent coating, and the light acquisition module collects the excitation light received on the quantum dot fluorescent coating. When a user approaches the quantum dot fluorescent coating, they may come into contact with it, causing detectable changes in the fluorescence intensity and light path of the contacted area. The light acquisition module collects these changes and outputs data such as light trajectory data and light intensity change data. Based on this data, it can be determined whether a cleaning event for the environment targeted by the cleaning system has been triggered. For example, based on the light trajectory and light intensity change data, it can be determined whether the user is simply passing by briefly or rubbing against the quantum dot fluorescent coating. If it is determined that the pet is rubbing against the quantum dot fluorescent coating, it can be determined that the pet wants to play; at this point, it can be further determined whether a cleaning event for the environment targeted by the cleaning system has been triggered.

[0037] Image acquisition sensors can be used to capture images of the environment and output image data. This image data can include information about the environment, as well as the pet's state, expression, and actions. Based on the pet's state, expression, and actions, it can be determined whether the pet wants to play; then, when it is determined that the pet wants to play, a cleaning event is triggered in the environment targeted by the cleaning system.

[0038] Sound acquisition sensors can be used to collect environmental sounds and output audio data; this audio data can include sounds made by the pet. By analyzing and converting the audio data, the pet's corresponding needs can be determined; when the need is for interaction or play, the cleaning event that triggers the cleaning system in the targeted environment can be determined.

[0039] In some embodiments, the target sensing data includes at least one of the following: capacitance change data, light trajectory data, light intensity change data, image data, and audio data.

[0040] Step 202: Determine the pet's emotional intentions based on the target sensor data.

[0041] After determining the target sensor data, the target sensor data can be identified to determine the pet's emotional intentions; emotional intentions can include: interactive intentions, playful intentions, resting intentions, etc.

[0042] In some embodiments, a model can be trained to predict a pet's emotional intentions based on sensor data; specifically, the model can be trained based on data of pet behavior collected daily and the corresponding emotional intentions of the pet. After obtaining the target sensor data, the target sensor data can be input into the model, which will identify the target sensor data and output the corresponding emotional intention of the pet.

[0043] In other embodiments, when there are multiple target sensing data, different target sensing data can be input into different models for prediction, and the emotional intention with the highest prediction ratio can be taken as the pet's current emotional intention. This application does not limit this.

[0044] In this application, by combining data from different sensors, the emotional intentions of pets can be effectively identified.

[0045] Step 203: When the emotional intention is an interactive intention, determine the cleaning event of the environment that triggers the cleaning system.

[0046] When the pet's emotional intention is determined to be an interaction intention with the cleaning system, it can be determined that the pet wants to play and interact at this time. At this time, it can be determined that the cleaning event that triggers the cleaning system can be triggered in the environment, and the pet can be used as a "living cleaner" to clean the environment.

[0047] Step 204: When a cleaning event is triggered in the environment targeted by the cleaning system, determine the cleaning path for that environment.

[0048] If no cleaning event is detected in the environment targeted by the cleaning system, step 201 can be performed to detect whether a cleaning event in the environment targeted by the cleaning system has been triggered.

[0049] Conversely, if a cleaning event is detected that triggers the cleaning system in the environment it targets, a cleaning path can be determined for that environment. For example, cleaning paths can be designed to cover areas such as under sofas, under beds, furniture crevices, and cat trees, in order to clean areas that cannot be reached by conventional cleaning systems.

[0050] Step 205: Determine the target projection image.

[0051] In some embodiments, different projection images can be designed, such as projection images of mice or butterflies. After determining the cleaning path, the current target projection image can be determined.

[0052] For example, different target projection images can be used for different types of pets; for example, for cats, the projection image of a mouse can be used as the target projection image.

[0053] For example, different projected images can be used as target projected images at different times to avoid pets getting tired of facing the same projected image for a long time.

[0054] Step 206: Project the target image according to the cleaning path.

[0055] After determining the target projection image, the target projection image can be projected onto the area corresponding to the cleaning path, and the target projection image can be controlled to move along the cleaning path; the pet attracted by the target projection image will move along the cleaning path, thereby cleaning these areas based on fur, paws, etc.

[0056] In some embodiments of this application, when projecting the target image according to the cleaning path, the following steps may also be included: Play target audio data corresponding to the target projected image at the current projection position; and / or, directionally project airflow at the current projection position of the target projected image.

[0057] In some embodiments, to prevent pets from losing interest and ceasing to chase the projected image, tactile and auditory feedback can be added.

[0058] Specifically, when projecting the target image along the cleaning path, target audio data corresponding to the target image can be played at the current projection position. For example, multiple audio playback units can be deployed in the environment. When the pet moves to a certain area, the audio playback unit corresponding to that area can be invoked to play the target audio data corresponding to the target image. For instance, if the target image is a projection of a mouse, the target audio data could correspond to the sound of a mouse.

[0059] In other embodiments, when projecting the target image along the cleaning path, airflow can be directionally projected at the current projection position of the target image to create an airflow pattern that would cause prey to escape, thereby increasing the pet's interest.

[0060] In some other embodiments, when projecting the target projection image according to the cleaning path, the target audio data corresponding to the target projection image can be played at the current projection position of the target projection image, and airflow can be directionally projected. This application does not limit this.

[0061] In this embodiment, data is collected from the pet to obtain target sensor data; based on the target sensor data, the pet's emotional intention is determined; when the emotional intention is an interactive intention, a cleaning event is determined to trigger the cleaning system for the environment; when the cleaning event is triggered, a cleaning path is determined for the environment; a target projection image is determined; and the target projection image is projected according to the cleaning path. Through this embodiment, different sensor data can be integrated to effectively identify the pet's emotional intention.

[0062] In addition, by increasing tactile and auditory feedback, pets can be prevented from losing interest and ceasing to chase the projected image.

[0063] Reference Figure 3 The diagram illustrates a flowchart of another pet-based cleaning method according to an embodiment of this application, which may include the following steps: Step 301: Obtain environmental pollution status information.

[0064] In this embodiment, the cleaning system may also be equipped with sensors for detecting the pollution status of the environment, such as millimeter-wave radar sensors and PM2.5 detectors. During operation, the cleaning system can determine the pollution status of the environment based on the information collected by these sensors, and determine whether to trigger a cleaning event for the environment targeted by the cleaning system based on the pollution status information.

[0065] The pollution status information may include location information and the degree of pollution in the area corresponding to that location.

[0066] Step 302: Based on the pollution status information, determine whether to trigger a cleaning event for the environment targeted by the cleaning system.

[0067] After obtaining pollution status information, the cleaning system can determine whether to trigger a cleaning event for the environment it is targeting based on the pollution status information.

[0068] For example, when a serious pollution event is determined to occur in a certain area of ​​the environment based on pollution status information, a cleaning event can be triggered for the environment targeted by the cleaning system.

[0069] For example, when it is determined that all areas of the environment are clean based on pollution status information, it can be determined that the cleaning event for the environment targeted by the cleaning system has not been triggered. This application embodiment does not limit this.

[0070] Step 303: When a cleaning event is triggered in the environment targeted by the cleaning system, determine the degree of pollution in each area of ​​the environment based on the pollution status information.

[0071] In some embodiments, after determining a cleaning event that triggers the cleaning system in the environment, the cleaning system can determine the degree of contamination in each area of ​​the environment based on the contamination status information. This contamination level information can be used to represent the degree of contamination in the area.

[0072] Step 304: Generate a cleaning path based on the pollution level information.

[0073] Based on pollution level information, cleaning paths can be constructed. Specifically, areas where the pollution level exceeds a preset value can be designated as mandatory points on the cleaning path, while areas where the pollution level does not exceed the preset value can be excluded from the cleaning path.

[0074] Step 305: Determine the target projection image.

[0075] In some embodiments, different projection images can be designed, such as projection images of mice or butterflies. After determining the cleaning path, the current target projection image can be determined.

[0076] For example, different target projection images can be used for different types of pets; for example, for cats, the projection image of a mouse can be used as the target projection image.

[0077] For example, different projected images can be used as target projected images at different times to avoid pets getting tired of facing the same projected image for a long time.

[0078] Step 306: Project the target image according to the cleaning path.

[0079] After determining the target projection image, the target projection image can be projected onto the area corresponding to the cleaning path, and the target projection image can be controlled to move along the cleaning path; the pet attracted by the target projection image will move along the cleaning path, thereby cleaning these areas based on fur, paws, etc.

[0080] In some embodiments of this application, when projecting the target image according to the cleaning path, the following steps may also be included: Play target audio data corresponding to the target projected image at the current projection position; and / or, directionally project airflow at the current projection position of the target projected image.

[0081] In some embodiments, to prevent pets from losing interest and ceasing to chase the projected image, tactile and auditory feedback can be added.

[0082] Specifically, when projecting the target image along the cleaning path, target audio data corresponding to the target image can be played at the current projection position. For example, multiple audio playback units can be deployed in the environment. When the pet moves to a certain area, the audio playback unit corresponding to that area can be invoked to play the target audio data corresponding to the target image. For instance, if the target image is a projection of a mouse, the target audio data could correspond to the sound of a mouse.

[0083] In other embodiments, when projecting the target image along the cleaning path, airflow can be directionally projected at the current projection position of the target image to create an airflow pattern that would cause prey to escape, thereby increasing the pet's interest.

[0084] In some other embodiments, when projecting the target projection image according to the cleaning path, the target audio data corresponding to the target projection image can be played at the current projection position of the target projection image, and airflow can be directionally projected. This application does not limit this.

[0085] In this embodiment, environmental pollution status information is obtained; based on the pollution status information, it is determined whether a cleaning event for the environment targeted by the cleaning system is triggered; when a cleaning event for the environment targeted by the cleaning system is triggered, the pollution level information of each area in the environment is determined based on the pollution status information; a cleaning path is generated based on the pollution level information; a target projection image is determined; and the target projection image is projected according to the cleaning path. This application guides a pet to move along the determined cleaning path, utilizing the pet's fur, paws, etc., to clean areas that the cleaning system cannot clean.

[0086] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of this application.

[0087] Reference Figure 4 This illustration shows a structural schematic diagram of a cleaning system according to an embodiment of this application. This cleaning system can utilize pet-based cleaning methods as mentioned in the above embodiments. Figure 4 As shown, the cleaning system 40 may include: The target sensing module 410 is used to collect sensing data on the environment targeted by the cleaning system 40. The control module 420 is used to determine whether a cleaning event for the environment targeted by the cleaning system 40 is triggered based on sensor data; when a cleaning event for the environment targeted by the cleaning system 40 is triggered, it determines a cleaning path for the environment; and guides the pet to move along the cleaning path to clean the environment. The guide module 430 is used to guide the pet to move along the cleaning path to clean the environment.

[0088] In this embodiment, the cleaning system 40 can be used to implement the pet-based cleaning method mentioned in the above embodiments; the cleaning system 40 may include a target sensing module 410, a control module 420, and a guidance module 430.

[0089] The target sensing module 410 can be used to collect sensing data on the environment targeted by the cleaning system 40; for example, the target sensing module 410 may include at least one of the following: A capacitive sensor is used to sense changes in an electric field and output capacitance change data. The light field touch sensor includes a quantum dot fluorescent coating, a light source unit, and a light acquisition module; the light source unit is used to emit excitation light to the quantum dot fluorescent coating; the light acquisition module is used to collect the excitation light received on the quantum dot fluorescent coating to obtain light trajectory data and / or light intensity change data. An image acquisition sensor is used to acquire images of the environment and output image data. A sound acquisition sensor is used to collect ambient sound and output audio data.

[0090] After the target sensor obtains the sensing data, it can send it to the control module 420. The control module 420 can determine whether to trigger a cleaning event for the environment targeted by the cleaning system 40 based on this sensing data.

[0091] For example, these sensor data may include the aforementioned target sensor data; based on the target sensor data, the control module 420 can identify the pet's emotional intentions, and when the emotional intention is an interactive intention, determine to trigger a cleaning event for the environment targeted by the cleaning system 40.

[0092] In another example, the control module 420 can determine pollution status information based on sensor data; based on the pollution status information, the control module 420 can determine whether to trigger a cleaning event for the environment targeted by the cleaning system 40. For example, when it is determined based on the pollution status information that a certain area of ​​the environment is severely polluted, it can be determined to trigger a cleaning event for the environment targeted by the cleaning system 40.

[0093] For example, when it is determined that all areas of the environment are clean based on the pollution status information, it can be determined that the cleaning event of the environment targeted by the cleaning system 40 has not been triggered. This application embodiment does not limit this.

[0094] After determining a cleaning event that triggers the cleaning system 40 in the environment it targets, the control module 420 can determine a cleaning path for that environment. For example, the cleaning path can be designed to cover areas such as under sofas, under beds, furniture crevices, and cat trees, so as to clean areas that the conventional cleaning system 40 cannot reach.

[0095] In another example, the control module 420 can use areas where the contamination level information exceeds a preset value as mandatory points on the cleaning path, and exclude areas where the contamination level information does not exceed the preset value from being mandatory points on the cleaning path. This application embodiment does not impose any restrictions on this.

[0096] After the cleaning path is determined, the guidance module 430 can guide the pet to move along the cleaning path. When the pet moves along the cleaning path and passes through the area corresponding to the cleaning path, the pet's fur, paws, etc. will clean these areas, thereby absorbing the pet's fur, dander, dust and other dirt in these areas, thus completing the cleaning of these areas in the environment.

[0097] In some embodiments of this application, the guiding module 430 includes: The projection unit is used to project the target image according to the cleaning path.

[0098] In some embodiments, a pet can be guided to move along a cleaning path by projection. Specifically, the projection unit can project a target image onto the area corresponding to the cleaning path and control the target image to move along the cleaning path; the pet attracted by the target image will move along the cleaning path, thereby cleaning these areas based on fur, paws, etc.

[0099] In some embodiments of this application, the guiding module 430 further includes at least one of the following units: The audio playback unit is used to play target audio data corresponding to the target projection image at the current projection position of the target projection image; The airflow projection unit is used to directionally project airflow at the current projection position of the target projection image.

[0100] In some embodiments, to prevent pets from losing interest and ceasing to chase the projected image, tactile and auditory feedback can be added.

[0101] Specifically, in addition to the projection unit, the guide module 430 may also include at least one of an audio playback unit and an airflow projection unit.

[0102] For the audio playback unit, when projecting the target image along the cleaning path, it can play target audio data corresponding to the target projected image at the current projection position. For example, multiple audio playback units can be deployed in the environment. When the pet moves to a certain area, the audio playback unit corresponding to that area can be invoked to play the target audio data corresponding to the target projected image. For example, if the target projected image is a projection of a mouse, the target audio data could correspond to the sound of a mouse.

[0103] For airflow projection units, when projecting a target image along a cleaning path, airflow can be directed to the current projection position of the target image to create an airflow pattern that resembles prey escaping, thereby increasing the pet's interest.

[0104] In some embodiments of this application, the cleaning system 40 further includes: An energy harvesting module is used to convert the pet's kinetic energy into electrical energy and supply it to the cleaning system 40.

[0105] In some embodiments, the cleaning system 40 may further include an energy harvesting module to convert the pet's kinetic energy into electrical energy and use it to power the cleaning system 40. The energy harvesting module may be a piezoelectric ceramic or a TENG (Triboelectric Nanogenerator), and this application embodiment is not limited to this.

[0106] In this embodiment, the cleaning system 40 includes: a target sensing module 410 for collecting sensing data of the environment targeted by the cleaning system 40; a control module 420 for determining, based on the sensing data, whether a cleaning event is triggered in the environment targeted by the cleaning system 40; determining a cleaning path for the environment when a cleaning event is triggered; guiding the pet to move along the cleaning path to clean the environment; and a guidance module 430 for guiding the pet to move along the cleaning path to clean the environment. By guiding the pet to move along the determined cleaning path, this application can utilize the pet's fur, paws, etc., to clean areas that the cleaning system 40 cannot clean.

[0107] The following, combined with Figure 5 , Figure 6 , Figure 7 and Figure 8 The following further explains the cleaning system and pet-based cleaning methods described above: First, it should be noted that this application relates to a method for achieving precise guidance and coordinated cleaning by perceiving the pet's status from multiple dimensions and combining it with human-computer interaction. This technical solution integrates micro-nano manufacturing, artificial intelligence, and Internet of Things technologies to construct a complete pet behavior management and environmental purification system.

[0108] Currently, pet air purifiers (i.e. cleaning systems) have formed a technological closed loop in the fields of intelligent behavior management, air purification, and human-computer interaction (voice control + AR training). They are being upgraded through the entire chain of "biological monitoring - environmental regulation - emotional interaction". Among them, millimeter-wave radar behavior analysis, germ elimination rate and multimodal interaction have become core competitiveness. However, cross-device data fusion and long-term behavior modeling are still technical bottlenecks to be overcome.

[0109] However, the following problems may still exist in the relevant technologies: Technical Issue 1: Limitations of Mechanical Interaction Mode: The interaction method is limited: Currently available laser cat toys can only attract cats' attention by moving a light spot, resulting in a relatively simple interaction method. While designs with decorative rings allow cats to directly touch and play, prolonged use can easily cause wear and tear on parts. Test data shows that the response speed of these traditional devices is generally slow, requiring more than 300 milliseconds for a response after a cat touches them.

[0110] The behavioral guidance effect is poor: when using laser to tease cats, the light spots appear randomly. In addition, the fixed design of the scratching post can cause cats to resist.

[0111] Technical Issue 2: Current biofeedback systems have two significant technical shortcomings: First, they are deficient in emotion recognition. The system lacks bioelectrical signal acquisition capabilities, making it unable to accurately capture the pet's true emotional state. The problem of misjudging emotions in existing solutions is quite serious. Second, the feedback mechanism is too rigid. The system uses fixed, preset interaction patterns and lacks intelligent learning capabilities. In actual use, it has been found that over 80% of pets gradually lose interest in the repetitive interaction methods after a period of use.

[0112] Technical Issue 3: The current system has energy and coordination issues, energy management needs to be optimized, the laser module consumes a lot of power, and the system lacks an energy recovery mechanism.

[0113] Technical Issue 4: Traditional robotic pet air purifiers and robot vacuums cannot get under sofas, beds, or furniture crevices, nor can they reach the top of cat trees or narrow corners. These places are often hiding places for pet hair, dander, and dust (high-pollution areas), resulting in: the house looks clean, but more and more "hidden corners" accumulate, becoming a breeding ground for allergens and bacteria.

[0114] Technical Issue 5: Air purifiers can only blow air and suck up dust, and are helpless against food scraps stuck to the floor, pet drool, flattened cat litter, and oily stains. Vacuum cleaners may remove some of the dirt, but stubborn stains often require manual scrubbing. As a result, the floor may appear dustier, but it still feels sticky and has spots, and hygiene concerns remain.

[0115] Technical Issue 6: To cover the entire house or powerfully purify a specific area, air purifiers / high-powered vacuum cleaners need to operate at high power for extended periods, consuming a lot of electricity and potentially generating noise. This results in increased electricity bills, and the noise may also annoy pets or the user.

[0116] Technical Issue 7: Traditional cleaning processes often require separating pets (for fear of injury or interference from the machine), or pets may cause disturbances during cleaning (chasing the robot vacuum or being bothered by the noise). The cleaning process itself does not benefit pets and may even cause stress. As a result, cleaning becomes a "confrontation" or "isolation" between humans and pets, with pets not getting exercise and potentially becoming destructive.

[0117] To address some of the aforementioned technical issues, this application proposes a light field touch-AR co-excitation technology: It employs quantum dot fluorescent coating technology, precisely controlling the size of the quantum dot fluorescent coating to within 100 nanometers; it is also equipped with a visual recognition system including a 1080P high-definition camera (i.e., image acquisition sensor) and an image processing chip, capable of keenly capturing relevant information. Meanwhile, the system's millimeter-wave radar sensor operates at a frequency of 60GHz, achieving a detection accuracy of ±1cm; and the miniature AR projection unit boasts a brightness of ≥500 lumens and a refresh rate of 120Hz, ensuring clear and smooth projection effects.

[0118] Application of the coating: This coating is applied to the interactive surfaces of the cleaning system, specifically the device surface of the pet purifier. When a pet approaches or lightly touches the pet purifier, this coating functions as the base layer for the photosensitive interaction. Function of the coating: The material basis for photosensitive interaction lies in precisely controlling the coating size to within 100 nanometers; precisely controlling the quantum dot fluorescent coating size to within 100 nanometers is the core principle. This involves optimizing the coating's optical response characteristics, sensing sensitivity, and stability to provide adaptability support for the core interaction technology of "light trajectory recognition," ultimately achieving precise interaction without physical contact. The specific reasons can be analyzed in detail from the following three aspects: 1. The core advantage of quantum dot fluorescent coatings lies in their size-dependent optical response capability—the fluorescence wavelength and luminescence intensity of quantum dots are directly related to their size, and they can only exhibit stable and efficient light absorption and fluorescence emission characteristics within a specific nanoscale range.

[0119] 2. The core requirement of light-sensing interaction is to "capture the subtle movements of a pet's slight touch," which requires the coating to have extremely high surface uniformity and sensing sensitivity. 100-nanometer scale control is the key to achieving these two points.

[0120] 3. Photosensitive interaction requires the coating to maintain stable performance during long-term use without affecting the function of other components of the device. 100-nanometer scale control can meet both of these requirements at the same time.

[0121] The core reason for precisely controlling the size of quantum dot fluorescent coatings to within 100 nanometers, laying the foundation for photosensitive interaction: The coating is adapted to the optical properties of quantum dots, ensuring stable and clear fluorescence signals to meet the signal capture requirements of light trajectory recognition. It guarantees a uniform and dense coating with high sensitivity, accurately capturing even the slightest touches from pets without any blind spots. Balancing coating stability with device compatibility, it does not interfere with other components such as capacitive sensors and millimeter-wave radar, supporting long-term reliable system operation. This lays a solid foundation for subsequent light-sensing interaction. The quantum dot fluorescent coating possesses unique optical properties (such as generating fluorescence at specific wavelengths upon light excitation and sensitivity to changes in light), and its stable microscopic scale ensures the accuracy of the optical response, a prerequisite for the realization of light trajectory recognition technology.

[0122] The system employs a dual interactive technology of "capacitive sensing + light trajectory recognition." When a pet lightly touches the surface of the device, the coating interacts with light, allowing the device to capture changes in the light trajectory caused by the pet's touch. After the system recognizes these changes in light signals, it can be converted into a judgment of the pet's "emotional intentions," ultimately achieving precise interaction without physical pressure or reliance on mechanical structures. This solves the pain points of traditional pressure sensors, such as easy damage and limited interaction.

[0123] The core reason why pet touch causes changes in light trajectory: The quantum dot fluorescent coating (scale ≤100nm) on the device surface forms a stable fluorescent signal layer, which triggers changes in light trajectory in two ways when a pet touches it: 1. Physical Obstruction / Pressure Influence: When a pet's paws or body parts touch the coating, they can obstruct the excitation light received by the coating (considering the application scenarios and technical characteristics of quantum dot fluorescent coatings, the excitation light here is mainly blue light (or ultraviolet light). Quantum dot fluorescent materials typically require high-energy photon excitation. The photon energy of blue or ultraviolet light matches the energy level difference of the quantum dots, effectively triggering their fluorescence emission. This is also a common type of excitation light source for quantum dots in display, sensing, and other fields. The excitation light is provided by a micro-light source module built into the light field touch-AR co-excitation system. This module may be integrated into the edge or inside the surface of an air purifier, forming a matching photosensitive system with the quantum dot fluorescent coating, continuously emitting excitation light to the coating to build a stable fluorescent signal layer), or it can change the local optical properties of the coating through slight pressure (the optical properties of the quantum dot fluorescent coating depend on the microstructure and energy level distribution of the quantum dots. The slight pressure generated by a pet's touch will apply stress to the coating, causing lattice distortion or energy level splitting of the quantum dots). Stress alters the electronic transition patterns of quantum dots, thereby affecting their optical response characteristics. This mechanism of stress-induced optical performance modulation is a typical physical characteristic of quantum materials at the nanoscale. The changes in optical properties caused by pressure are mainly manifested as changes in fluorescence intensity and shifts / scattering of the light path. On the one hand, lattice distortion reduces the fluorescence emission efficiency of quantum dots, leading to a weakening of fluorescence intensity in the contact area; on the other hand, pressure alters the local refractive index distribution of the coating, causing detectable changes such as bending and scattering in the propagation paths of excitation light and fluorescence (the system identifies pet touch actions by capturing these changes). This results in detectable changes in fluorescence intensity and the light path (the light path refers to the path of light propagation in the quantum dot fluorescent coating and surrounding medium, including the propagation path of excitation light from the built-in light source to the coating, and the path of fluorescence generated by the quantum dot after excitation to the system detection module. Changes in the light path directly affect the reception and recognition of fluorescence signals and are the core observation object of optical trajectory recognition technology). 2. System Collaborative Capture: A high-definition camera and an image processing chip monitor the fluorescent signal of the coating in real time. The movement trajectory of the pet when it touches it (such as light touch or swiping) will be converted into continuous changes in light signals, which will be accurately captured and identified by the system as "light trajectory data".

[0124] The light trajectory associated with a pet's intention is the core basis for the system to recognize a pet's intention, which is essentially a transformation of "action - signal - intention": 1. A pet's initiative to touch (such as lightly touching or pawing at the device) is a direct manifestation of its "willingness to interact"—a pet will only initiate contact when it is curious about the device and wants to play with it; 2. The system further judges the intensity of the pet's intention by the shape of the light trajectory (such as single touch, continuous swipe) and speed: for example, rapid continuous swipes can represent "strong desire to play", while a single light touch can represent "initial curiosity"; 3. Based on emotional intent, the system initiates subsequent feedback (such as projecting virtual prey or triggering sound effects), forming an interactive closed loop of "pet expressing its wishes → system response", making the interaction more precise and tailored to the pet's needs.

[0125] Core function: The basics of photosensitive interaction: By utilizing the fluorescence properties of quantum dots, light signals are converted into recognizable electrical signals, enabling the system to accurately sense the approach or touch of a pet.

[0126] Motion trajectory interaction: When a pet makes specific movements (such as waving or waving) near the device, the system captures the motion trajectory through visual recognition to transmit interactive commands (such as switching game modes). Combined with capacitive sensing and light trajectory recognition technology, it achieves precise interaction without physical contact (such as recognizing a pet's paw touch). AR projection optimization: Provides a better optical reflective surface for micro AR projection units (≥500 lumens brightness) to improve projection clarity.

[0127] This coating forms a complete interaction chain with other components of the system: Pet contact → Quantum dot coating for photosensitivity → Camera / radar positioning → AR projection feedback → Multimodal interactive response.

[0128] This application employs both capacitive sensing and light trajectory recognition technologies to achieve precise interaction without physical contact. Pets only need to approach or lightly touch the device surface for the system to accurately identify their behavioral intentions.

[0129] In addition, the system transforms tedious cleaning tasks into an engaging hunting game for pets. It intelligently adjusts the movement trajectory of virtual prey based on real-time environmental data, ensuring that pets naturally cover highly polluted areas during the game.

[0130] In addition, this application also involves a multimodal feedback mechanism: integrating visual (AR projection), auditory (ambient sound effects), and tactile (airflow changes) feedback channels to create an immersive interactive experience.

[0131] This application not only improves the cleaning coverage of polluted areas, but also significantly extends the duration of a single interaction with pets compared to traditional solutions, while reducing the rate of accidental device triggering.

[0132] This application addresses the problems of traditional air purifiers: firstly, they rely on mechanical buttons or pressure sensors, resulting in limited and easily damaged interaction methods; secondly, they lack effective incentive mechanisms, leading to low pet participation. This system solves these problems through light field touch control and AR incentive technology, specifically: For this application, the solution to the core problem 1, stubborn dead corners that cannot be cleaned, is as follows: Using pets as "living cleaners," they can squeeze into any corner that machines can't reach. The system controls the "prey" (i.e., the projected image of the target) to run into these blind spots, and the pets naturally follow, using their bodies (rubbing) and paws (stepping and rubbing) to remove dust and dirt. This completely eliminates cleaning blind spots, leaving under beds and sofa crevices spotless.

[0133] For this application, the solution to the core issue 2, the difficulty in removing sticky stains, is as follows: Pets' paws are natural lint rollers. When they chase and trample, the texture of their paw pads and static electricity can pick up stubborn stains (food scraps, drool stains, oil stains) that vacuum cleaners can't pick up or air purifiers can't blow away.

[0134] For this application, the solution to the core issue 3, pet destruction / excessive energy, is to channel the pet's excess energy into "work" (chasing prey).

[0135] For this application, the solution to the core issue 4, high energy consumption / low efficiency, is as follows: Intensive cleaning is only activated in the detected high-pollution areas, while other areas consume no power. In other words, the system monitors the pollution status of various areas indoors in real time through sensors (air quality sensors, dust detection modules, high-definition cameras, etc.), accurately locating high-pollution areas (such as areas with excessive dust concentration, food residue / pet hair accumulation); Intensive cleaning mode is activated only in high-pollution areas: core functions such as AR projection (high-brightness projection of virtual prey) and multimodal feedback (sound effects + airflow) are activated simultaneously to guide the pet to focus on cleaning that area; in areas where no pollution or low pollution is detected, the device only retains basic sensing functions (low-power operation), without activating power-consuming modules such as AR projection and intensive airflow, generating almost no additional energy consumption, achieving "zero power waste in non-clean areas".

[0136] For this application, the system is equipped with high-precision sensors and intelligent recognition modules, which can distinguish between polluted areas and clean areas in real time. The air quality sensor and dust detection module can quantify the pollution concentration, and the high-definition camera + millimeter-wave radar (±1cm accuracy) can locate the coordinates of the polluted area, providing data for "precision cleaning" and avoiding blind operation. Furthermore, the cleaning process in this application relies on the pet's "bioenergy" (chasing motion) rather than on the device's full-area mechanical cleaning (such as the continuous blowing of a traditional air purifier or the moving cleaning of a vacuum cleaner). The system only needs to guide the pet to the highly polluted area through low-power methods such as AR projection to complete the cleaning, without consuming electricity to clean the unpolluted area; Furthermore, this application can incorporate the posture recognition algorithm of the self-powered behavior response module, allowing the system to automatically switch power consumption modes based on the pet's location and pollution status—activating normal operation mode in high-pollution areas when the pet is nearby; switching to low-power mode when there is no pollution or the pet is far away, thus avoiding ineffective energy consumption. Pet movement provides "bioenergy." Benefits: energy and cost savings, significantly improved efficiency.

[0137] For this application, the solution to the core issue 5, the conflict between humans and pets during the cleaning process, is as follows: users don't need to crawl on the floor to clean hard-to-reach corners or laboriously scrub the floor; they simply start a game. Pets enjoy playing and receive rewards (such as automatically being fed treats after the game), thus achieving a more harmonious relationship between humans and pets.

[0138] In addition, the cleaning system of this application is also equipped with a composite energy harvesting device, which may include a piezoelectric ceramic with a conversion efficiency of not less than 25% and a TENG with an output power of not less than 0.5mW / cm². A TENG is a novel energy harvesting device that converts mechanical energy (such as friction, vibration, etc.) into electrical energy based on the triboelectric effect and electrostatic induction effect. Therefore, this application can convert the natural behaviors of pets (such as scratching and running) into usable electrical energy, achieving energy self-sufficiency for the equipment.

[0139] Furthermore, it can automatically switch working modes based on the pet's activity level, maximizing energy efficiency while ensuring effectiveness. For example, the cleaning system operates when the pet is active and enters sleep mode when the pet is resting.

[0140] In addition, this application integrates multiple energy harvesting technologies to ensure stable power supply in different scenarios. This not only reduces the average daily standby power consumption but also improves energy self-sufficiency and extends the device's battery life.

[0141] The cleaning system of this application can also be equipped with a lightweight VR rendering engine, with a single frame rendering time controlled within 10ms; the digital twin modeling tool equipped with it has a modeling error of no more than 5%; at the same time, the platform is set up with edge computing nodes with a computing power of 5 TOPS or more; the smart contract platform supports ERC-721 and ERC-1155 protocols to meet diverse application needs.

[0142] This application utilizes digital twin technology to map virtual training results onto physical devices, forming an integrated online and offline training system. It also digitizes pet behavior data into NFTs (Non-Fungible Tokens), establishing a digital asset circulation ecosystem. Furthermore, it designs cross-pet collaborative tasks to enhance user stickiness and engagement. This not only improves user engagement but also increases training efficiency and user retention.

[0143] Additional explanation: NFTs are digital assets based on blockchain technology. Their core feature is "non-fungible" – each NFT has a unique identifier, is indivisible, and is non-substitutable. They can be used to establish ownership and facilitate the circulation of specific digital content (such as data, images, virtual items, etc.).

[0144] In the cleaning system described in this application, the core application of NFTs is "pet behavior data assetization": data on pets' cleaning interactions on physical devices (such as the trajectory of chasing virtual prey, cleaning coverage efficiency, and completed cleaning tasks) are collected and organized, and then forged into unique NFTs through a smart contract platform (protocol). These NFTs can serve as "digital badges" for users to display their pets' cleaning achievements, and can also be traded within the platform's digital asset circulation ecosystem, generating additional value from the pets' interactions and further enhancing user engagement and retention rates.

[0145] Figure 5 The diagram illustrates the operation flow of the pet air purifier according to an embodiment of this application: User initialization settings: This covers user configuration via mobile APP and operation via the Metaverse platform, providing parameter and strategy support for the operation of physical devices.

[0146] Device operating parameters: virtual prey type (such as mouse, butterfly, bird, etc.) (i.e., projected image), AR projection brightness (adapting to different indoor lighting), maximum game time (to avoid pet over-fatigue), cleaning sensitivity (pollution concentration threshold, such as activating strong guidance when dust concentration ≥0.3mg / m³). Pet matching parameters: pet breed (cat / dog), size (small / medium / large), mobility (active / gentle / lazy), used to match the movement speed of virtual prey (e.g., 0.4m / s for small cats, 1.2m / s for large dogs), and trajectory complexity; Reward rules parameters: Trip trigger conditions (e.g., feeding after cleaning 3 highly polluted areas), feeding amount (set according to pet size), NFT generation threshold (e.g., digital badges can be generated if a single cleaning session lasts ≥15 minutes).

[0147] Core strategy (user-plann execution logic that provides action guidance for the device); Cleaning path strategy: Virtually train preset cleaning priorities through the metaverse platform (such as "living room first, then bedroom" or "prioritize dead corner areas"), or set key cleaning areas (such as around pet food bowls or under sofas). Interactive incentive strategies: solutions for when pet interest declines (such as switching virtual prey types, enhancing sound effects / airflow feedback), and reward combinations for pets after completing cleaning tasks (such as "treats + pheromone soothing"). Energy consumption control strategy: Low power mode trigger conditions (such as switching after the pet is away from the device for 5 minutes), energy harvesting priority (prioritizing the capture of mechanical energy generated by the pet scratching / running); Data assetization strategy: NFT generation rules (such as unlocking limited NFTs after the first full cleaning coverage, and monthly cleaning efficiency ranking NFTs), and permission settings for displaying metaverse transactions (public display / visible only to friends).

[0148] Additional explanation: These parameters and strategies are the core link connecting user needs, pet characteristics, and device functions. After users complete the configuration through the mobile app or Metaverse platform, the physical device will run precisely according to these settings. For example, if a user sets "virtual prey = butterfly" (parameter) and "trajectory complexity = low + feed a treat once every 5 minutes" (strategy) for their lazy small cat, the device will generate a slowly moving butterfly trajectory and guide the cat to complete the cleaning with timed rewards. If the user presets "prioritize cleaning the dead corners of the balcony" (strategy) through the Metaverse platform, the physical device will synchronize the route to the AR incentive system and prioritize guiding the pet to the target area, ensuring that the device operation is completely in line with the user's needs and the pet's condition.

[0149] When configuring the mobile app, you can set the type of virtual prey / game difficulty, etc.; you can also enable the device's automatic mode.

[0150] During the operation of the Metaverse platform, virtual pet / device digital twin models can be created and trained in virtual scenes to plan cleaning paths.

[0151] System startup: The three core modules (light field touch-AR, self-powered, and metaverse virtual-real mapping) have completed hardware readiness and technical preparation.

[0152] Specifically, for light field touch-AR, it is possible to detect whether light field touch-AR is ready; specifically, light field touch-AR may include a quantum dot fluorescent coating to support light sensing, and may also include a camera + millimeter-wave radar to activate environmental perception.

[0153] Self-powered energy can be achieved by first ensuring the piezoelectric ceramics are deployed and the supercapacitors are activated for energy storage.

[0154] In the metaverse virtual-real mapping, computing power can be provided by edge computing nodes, and the virtual-real mapping can be completed by digital twin modeling; Pets can generate mechanical energy through scratching, running, and rubbing against devices, which is then converted into electrical energy via piezoelectric ceramics and TENG and stored in a supercapacitor.

[0155] When generating clean paths, information about the pollution status of the environment and the metaverse training scheme can be combined.

[0156] Perception and Interaction Trigger: By fusing multiple sensors to perceive the pet's and the environment's status, and combining "capacitive sensing + light trajectory recognition" to achieve contactless interaction trigger, it serves as the entry point for the system to respond to pet behavior.

[0157] The perception and interaction triggering process can include sensor detection, behavioral intent recognition, energy harvesting and mode switching, AR stimulation and cleaning execution.

[0158] Sensor detection can include cameras capturing the pet's position / posture, as well as information on environmental pollution levels. The data detected by the sensors can be used by posture recognition algorithms to determine the pet's condition. Millimeter-wave radar can also be used to sense changes in the pet's distance / position.

[0159] Behavioral intent recognition can use capacitive sensing to detect a pet approaching and light trajectory recognition to capture a pet's light touch.

[0160] Energy harvesting and mode switching can include mechanical energy harvesting, plan generation, and intelligent mode switching. During plan generation, a posture recognition algorithm can first determine the pet's status. The cleaning path can be intelligently adjusted during plan generation.

[0161] During intelligent mode switching, the system can enter low-power mode when the pet is away from the system, and enter normal operation mode when the pet is near the system, i.e., normal operation.

[0162] Operational layer: It implements two core functions in parallel: "energy self-sufficiency" and "cleaning execution" - the energy harvesting module converts pet behavior into electrical energy and intelligently switches power consumption modes, and the AR incentive system guides the pet to complete the cleaning task.

[0163] AR-based stimulus and clean execution can generate solutions and output multimodal stimuli. Multimodal stimuli output can include AR projection, sound, airflow, etc.

[0164] Pet cleaning behaviors can manifest as: pets chasing prey, cleaning highly polluted areas, and rubbing their bodies or stomping on surfaces to remove stains or hard-to-reach areas. Pet behavior can be digitized using NFTs (Network FTs).

[0165] In data feedback and resource utilization, real-time data monitoring can be performed and displayed on the app. Digital asset processing can also be conducted, and these digital assets can be circulated / displayed on the Metaverse platform.

[0166] On the one hand, it synchronizes equipment operation and cleaning effect data with users; on the other hand, it converts pet behavior data into assets, forming a closed loop of "use-feedback-value-added".

[0167] The system collects multi-dimensional data on pets' approach, touch, actions, and vocalizations through various devices such as capacitive light trajectory recognition, high-definition cameras, and microphones. This data is then fused using multimodal methods to identify emotional intentions and input into an AI decision engine. Combining game-like elements with emotional logic, the system selects multiple feedback channels (treats, pheromones, etc.) and generates and adjusts virtual prey, which is then presented and guided by AR projection to help the pet cover contaminated areas. Powered by an energy harvesting module, the data is transmitted to the network via LoRa. Users can view the data and redeem items through a mobile app. Pet behavior is digitized into NFTs and traded in the metaverse, achieving a virtual-to-physical mapping and constructing a complete process from data collection to interaction.

[0168] Figure 6 The diagram shows a schematic of a light field touch-AR co-excitation system according to an embodiment of this application: After the system starts up, it first initializes hardware such as quantum dot fluorescent coating, high-definition camera + image processing chip, 60GHz millimeter wave radar, and miniature AR projector for environmental and pet perception.

[0169] If a pet is detected approaching, its emotional intentions are identified through capacitive sensing light trajectory. Combined with the game difficulty and virtual prey type (i.e. projection type) set in the mobile app, and based on real-time monitoring data of the polluted area, the virtual prey trajectory (i.e. cleaning path) is intelligently adjusted. The AR projection guides the pet to cover the highly polluted area. Then, through multimodal feedback such as the ground AR scene (visual), prey calls / environmental sound effects (auditory), and the simulated wind feeling from the purifier (tactile), the pet interaction time is extended and the cleaning coverage is improved. Users can view the interaction data and purification progress on their mobile phones. Ultimately, the system is continuously optimized to achieve the goal of cleaning polluted areas through pet interaction.

[0170] Figure 7 The diagram illustrates the self-powered behavior response of an embodiment of this application: After the system starts up and completes the initialization of the energy harvesting device (including the initialization of piezoelectric ceramics, TENG, supercapacitors, and attitude recognition algorithms), it first performs behavior perception and energy harvesting, and determines whether the pet has touched or approached. If not, it enters a low-power standby mode and continuously detects whether the pet approaches again. If so, the attitude recognition algorithm is run to identify the pet's specific behavior, and then the energy harvesting mode is activated to convert mechanical energy into electrical energy and store it. Through the hybrid power supply architecture (piezoelectric ceramics and TENG), the system integrates and outputs a stable power supply to the air purifier. It can also intelligently switch operating modes: low power consumption when the pet is far away and normal operation when the pet is close. Relevant data can be viewed in real time on the mobile phone, and the system is continuously optimized to reduce standby power consumption and extend battery life.

[0171] Figure 8 The diagram illustrates the operation of the metaverse training extension platform according to an embodiment of this application: After users launch the platform and complete initialization (initialization of the lightweight VR rendering engine, digital twin modeling tools, edge computing nodes, smart contract platform, etc.), they log in via their mobile phones after identity verification and enter the virtual-real linkage training portal to build a virtual scene, generating a physical environment, a digital twin of an air purifier, and a virtual pet. Then, virtual training begins, and users control the virtual air purifier and pet to move along a route. The training results are synchronized to the physical air purifier through digital twin mapping to guide the real pet. On the other hand, the pet's behavior data is digitized into NFTs to build a digital asset circulation ecosystem, and the platform trades / displays NFE assets.

[0172] The core of this process is to build a closed-loop ecosystem of "online virtual training → offline physical execution → data asset value enhancement." Essentially, it uses metaverse technology to allow users to plan cleaning strategies in advance, giving pet behavior additional value, and enhancing engagement through community interaction. This can be broken down into three things: 1. After logging in, users will have a 1:1 digital twin model built based on their real home environment and physical air purifier. A virtual pet corresponding to their pet will also be generated—essentially replicating the complete "home + device + pet" scenario in the metaverse. Users can then "pre-plan cleaning" in the virtual scene: for example, planning a cleaning path like "under the living room sofa first → then the corner of the dining room," setting the movement trajectory of virtual prey, and controlling the virtual pet to practice chasing. This step helps users design an efficient cleaning plan in advance, avoiding the pet running around haphazardly in the physical environment.

[0173] 2. The virtual training routes and prey trajectories will be synchronized to the physical air purifier in your home via digital twin technology. The physical device will directly use the virtual solution, projecting the corresponding AR virtual prey to guide your real pet to chase along the preset route, accurately covering highly polluted areas—essentially "training the solution online and using it directly offline," eliminating the need for repeated adjustments to the physical device and improving cleaning efficiency.

[0174] 3. After a real pet completes cleaning according to the virtual plan, its chasing trajectory, cleaning coverage, interaction time and other behavioral data will be minted into unique NFTs (non-fungible tokens), which will become digital assets that users can display and trade, giving the pet's cleaning behavior additional value. The platform also supports multi-user teams, allowing multiple virtual pet avatars to collaborate on cleaning tasks. Combined with community incentives (such as rankings and virtual rewards), users can not only "manage their own home's cleanliness" but also participate in social interactions, thus making them more willing to continue using the platform.

[0175] Throughout the process, users can monitor "virtual training progress, NFT asset status, and physical equipment cleaning effects" in real time via their mobile phones, forming a cycle of "planning → execution → feedback → optimization." This makes cleaning more precise and efficient, and also makes the process more fun and valuable. Users can also engage in cross-pet collaboration and multi-user team tasks, combined with community incentives to enhance user stickiness. At the same time, users can view training progress, virtual assets, and physical equipment operation status in real time on their mobile phones, helping the platform to continuously optimize to improve training efficiency and user retention.

[0176] In terms of coating treatment, this application utilizes quantum dot fluorescent coating technology and, through precise process control, strictly controls the coating size to within 100 nanometers, which lays a good foundation for subsequent photosensitive interaction.

[0177] For visual recognition, it is equipped with a high-definition camera and a dedicated image processing chip. The high-definition camera can clearly capture the pet's movements and surrounding environment information. For example, when the pet approaches the air purifier, the camera can record the pet's position and posture changes in real time. The image processing chip quickly analyzes and processes the images captured by the camera, and keenly identifies relevant key information. The application of millimeter-wave radar sensors is also crucial. Operating at a frequency of 60GHz, these sensors achieve a detection accuracy of ±1cm, precisely sensing the distance and positional changes between the pet and the device. The miniature AR projection unit boasts a brightness of ≥500 lumens and a refresh rate of 120Hz. The high brightness ensures clear visibility of the projected content in various lighting conditions, while the high refresh rate delivers smooth and natural visuals, preventing stuttering. In terms of interaction design, it breaks through the limitations of traditional pressure sensors, employing a dual technology of capacitive sensing and light trajectory recognition. When a pet approaches the device surface, capacitive sensing technology can detect the pet's presence; if the pet lightly touches the device, light trajectory recognition technology can capture the pet's movement, thereby accurately identifying the pet's behavioral intentions and achieving precise interaction without physical contact. For example, if a pet lightly touches the surface of an air purifier with its paw, the system can recognize that the pet has a desire to interact.

[0178] To enhance pet engagement, the system transforms tedious cleaning tasks into an engaging hunting game. Users can pre-set the game difficulty and virtual prey type via a mobile app. The system monitors environmental data in real time and intelligently adjusts the virtual prey's trajectory based on information such as the distribution of polluted areas, guiding pets to naturally cover highly polluted areas while chasing virtual prey. For example, when pollution levels are high in a corner of the living room, the virtual prey will be more active in that area, attracting the pet. Simultaneously, the system integrates visual, auditory, and tactile feedback channels to create an immersive interactive experience. Visually, virtual scenes and prey are projected onto the ground using AR; auditorily, ambient sound effects, such as prey calls, are emitted from the air purifier's built-in speakers; tactilely, the device generates airflow changes, blowing gentle breezes from the purifier's vents to simulate the wind generated by the running prey. Addressing the issue that "hearing and touch feedback are fixed to the air purifier, making it difficult to guide pets away from the device," this system optimizes the process using "dynamic tracking + directional transmission" technology. This allows auditory and tactile feedback to be synchronized with the AR virtual prey's trajectory, ensuring that "wherever the prey runs, the feedback follows," effectively guiding pets away from the device's vicinity and towards highly polluted areas. Auditory feedback: directional sound effects + trajectory synchronization, simulating the sound of prey moving: Directional sound technology: The device has multiple built-in miniature directional speakers (instead of a single speaker) distributed in different positions on the air purifier body. Combined with 60GHz millimeter-wave radar (±1cm accuracy) to track the AR projection coordinates of virtual prey in real time, the algorithm controls the speakers in the corresponding positions to emit sound, and the sound intensity is dynamically adjusted with the distance of the prey - the farther the prey is from the air purifier, the volume of the speaker in the corresponding direction is appropriately increased (while still maintaining a comfortable decibel level for the pet), avoiding the sound being concentrated at the device.

[0179] Sound effect trajectory matching: The movement speed and actions of the virtual prey are precisely synchronized with the sound effects: When the prey runs fast, the sound effects present a "continuous and progressive" pattern (such as "squeaking" from weak to strong and then back to weak, simulating the auditory changes of the prey approaching - passing by - moving away); when the prey stays in a blind spot, the sound effects switch to "intermittent soft sounds" to attract the pet to clean more thoroughly.

[0180] Example: When the "mouse" projected by AR runs from next to the air purifier to under the sofa 5 meters away, the directional speaker near the sofa activates, emitting a gradually clearer "squeaking" sound, while the volume of the air purifier's main speaker decreases, guiding the cat to follow the sound to the underside of the sofa instead of staying around the device.

[0181] Haptic feedback: Directional airflow projection + trajectory linkage, simulating the wind sensation of prey running. Steering airflow jet module: The air purifier outlet is equipped with a micro electric steering mechanism (steering angle 0-180°), which works in conjunction with the AR projection unit and millimeter-wave radar to receive the location coordinates of the virtual prey in real time and drive the air outlet to precisely turn in the direction of the prey's movement, so as to achieve "airflow deflection synchronously with the prey's trajectory".

[0182] Dynamic airflow intensity adaptation: Based on the distance between the pet and prey captured by the high-definition camera, the airflow intensity is adjusted: when the prey is close to the pet (≤1 meter), the airflow intensity is reduced (to avoid startling the pet); when the prey guides the pet to move towards a distant high-pollution area, the airflow intensity is moderately increased to form a "continuous wind traction" so that the pet can perceive that "the airflow generated by the prey's movement" is always in front of it.

[0183] Example: When the virtual "mouse" moves from the purifier to the corner of the restaurant (high-pollution area), the air outlet is directed towards the restaurant via a steering mechanism, slowly deflecting along the "mouse's" trajectory and continuously blowing out a gentle airflow; at the same time, the airflow intensity is gradually adjusted according to the distance the "mouse" moves, so that the dog always feels that there is "wind driven by prey" in front of it, and actively follows it to the corner of the restaurant.

[0184] Core technology support: ensuring precise synchronization of hearing, touch, and trajectory. Multi-module low-latency linkage: The core processing chip of the light field touch-AR system adopts a "parallel computing architecture" to simultaneously receive the AR projection trajectory coordinates and the pet / prey location data from millimeter-wave radar. The response latency for driving directional auditory sound and tactile airflow direction is ≤20ms, which is perfectly matched with the 120Hz refresh rate AR projection, avoiding the disconnect problem of "the prey has run far away, but the feedback is still at the device".

[0185] Intelligent adjustment of distance threshold: The system presets a "feedback following threshold" (e.g., when the virtual prey is ≥1 meter away from the purifier, directional hearing + airflow is activated; when it is ≤1 meter away, the basic feedback of the device itself is maintained), which ensures the effectiveness of the feedback when the pet is far away from the device, while avoiding excessive interference from the feedback when it is close.

[0186] Through multimodal collaboration of "AR visual guidance + directional auditory tracking + tactile steering," pets can no longer be limited to the vicinity of the air purifier, but can be precisely guided to any highly polluted area indoors (including places far from the device such as under the bed, sofa crevices, and corners of the dining room). In the implementation example, the sofa is 3 meters away from the air purifier. After the AR projection of the "mouse" extends to the sofa, the directional speaker emits sound at the same time, and the air outlet turns to spray airflow towards the sofa. The three of them form a three-dimensional guidance of "visual + auditory + tactile", which makes the cat actively leave the air purifier and chase to the sofa to complete the cleaning. From a data perspective, this design increases the percentage of cleaning time spent with pets away from the device (≥1 meter) from 30% in traditional fixed feedback to 85%, and increases the cleaning coverage rate of highly polluted areas (mostly away from the device) by more than 60%, completely solving the problem of "pets staying close to the device".

[0187] The core optimization logic of auditory and tactile feedback is to shift from fixed device output to dynamic, directional output that follows the prey's trajectory, forming a closed loop with AR vision. This ensures that pets always perceive that "the prey is actually present in the distant polluted area," thus encouraging them to actively go for cleaning while maintaining an immersive interactive experience. This multimodal feedback mechanism not only improves the cleaning coverage of polluted areas but also significantly extends the duration of a single pet interaction compared to traditional solutions, while reducing the rate of device false triggers. It effectively addresses the pain points of traditional air purifiers, such as their simplistic and easily damaged interaction methods and low pet participation. Users can also view their pet's interaction and the air purifier's purification progress in real time on their mobile phones.

[0188] Implementation Example: Users set a virtual "mouse," a favorite of their cat, as their virtual prey via a mobile app and activate automatic mode. When the air purifier detects excessive pollution levels under the living room sofa, an AR projection immediately displays the "mouse's" running trajectory around the sofa. Upon seeing this, the cat actively chases after it. During this process, the purifier tracks the cat's position in real-time using cameras and radar, adjusting the "mouse's" route to always stay around the polluted area. Simultaneously, a speaker emits a slight "squeaking" sound, and the air outlet blows air in the direction the "mouse" moves. After 20 minutes, the mobile app shows that the pollution level in the area has decreased by 60%, and the cat still has the energy and intention to interact.

[0189] Self-powered behavior response module: The self-powered behavior response module is equipped with a composite energy harvesting device, which includes a piezoelectric ceramic with a conversion efficiency of no less than 25% and a TENG (triboelectric nanogenerator) with an output power of no less than 0.5mW / cm². These devices are installed on the sides and bottom of the air purifier, in locations easily accessible to pets. These two energy harvesting devices effectively collect energy from the environment, such as the mechanical energy generated when a pet scratches or runs near the air purifier, converting it into electrical energy to power the device. The supercapacitor energy storage unit has a cycle life of over 100,000 cycles, ensuring stable energy storage and release.

[0190] The module's posture recognition algorithm supports the classification and recognition of more than 10 typical actions, accurately sensing various pet behaviors such as rubbing against or patting the device. When these behaviors are detected, the system activates energy harvesting mode. This module achieves behavioral energy conversion, transforming the energy generated by the pet's natural behavior into usable electrical energy, enabling the device to be self-sufficient in energy.

[0191] Based on the pet's activity level, the module can automatically switch operating modes to maximize energy saving while ensuring purification effectiveness, thus forming an intelligent operation mode. When the system detects that the pet is moving away from the device through sensors, the air purifier will enter a low-power mode; when the pet approaches or moves around, the device will automatically switch to normal operating mode.

[0192] The core difference between normal operating mode and low power mode: The core triggering conditions are different: Normal operating mode: Automatically triggered when the sensor (camera + millimeter-wave radar) detects that a pet is approaching the device (distance ≤ 5-10cm), moving around the device, or has a clear intention to interact (such as lightly touching the device surface).

[0193] Low power mode: Automatically switches when the sensor continuously confirms that the pet is away from the device (distance > 10cm) and inactive for 5 minutes or more.

[0194] The activation status of the functional modules is different: Normal operating mode: The core modules such as the light field touch-AR system, multimodal feedback (directional hearing, directional touch), high-efficiency energy harvesting (piezoelectric ceramic + TENG), and precise monitoring (high-frequency camera + radar) are fully activated, forming a complete closed loop of interaction-guidance-cleaning-energy harvesting.

[0195] Low power mode: Only basic sensing functions are retained, including low-frequency environmental pollution monitoring and pet proximity detection. All non-essential modules such as AR projection, directional sound effects, airflow jets, and high-efficiency energy harvesting are put into hibernation.

[0196] The operating logic and parameters are different: Normal operating mode: High-frequency monitoring (10 times / second) is used to capture the pet's location, posture and pollution data in real time, and dynamically adjust the virtual prey trajectory and feedback intensity; the energy harvesting device is efficiently triggered, and the supercapacitor is dynamically charged and discharged to ensure the continuous operation of core functions.

[0197] Low power mode: Low-frequency monitoring (1 time / minute) is used to maintain only the lowest frequency of sensing needs and avoid unnecessary power consumption; energy is only supplied to basic sensing, the supercapacitor stops actively charging and only retains the existing power to support standby.

[0198] The core objectives and energy consumption levels are different: Normal operating mode: The core objective is to achieve pet interaction guidance and precise cleaning, while simultaneously collecting mechanical energy and converting it into electrical energy, balancing cleaning efficiency and pet experience; energy consumption is at a moderate level, relying on a self-powered system to achieve energy self-sufficiency.

[0199] Low power mode: The core objective is to minimize energy consumption and extend device battery life, maintaining only basic standby awareness; energy consumption is extremely low, with daily power consumption reduced by more than 60% compared to normal mode.

[0200] Different user-perceived performance Normal operating mode: The device provides clear feedback such as AR projection screen lighting, directional sound output, and airflow following the prey. The mobile APP can update the pet's interaction status, cleaning progress, and energy self-sufficiency data in real time.

[0201] Low power mode: The device indicator light is dim or off, and there is no output such as projection, sound effects, or airflow. The mobile APP only synchronizes the device's basic power consumption status and standby battery life.

[0202] What does normal operating mode look like? Normal operating mode is a "full-function collaborative state" activated by the device in response to pet activities and to efficiently complete cleaning tasks. The core is to activate all core modules related to interaction, guidance, and cleaning, while dynamically adjusting operating parameters based on real-time data to ensure that "pet interaction is responsive, cleaning guidance is effective, and energy use is efficient." Specifically, the core functional modules are fully activated, supporting a closed loop of interaction and cleaning.

[0203] The light field touch-AR collaboration module is running at full capacity: The quantum dot fluorescent coating and capacitive sensing / light trajectory recognition technology maintain "high sensitivity response". The system can instantly recognize a pet when it is slightly close (within 5-10cm) or touches the device. The miniature AR projection unit operates at full power with lumens brightness and refresh rate, projecting clear and smooth virtual prey trajectories in real time, and dynamically adjusting according to the distribution of polluted areas and the location of the pet. High-definition cameras and 60GHz millimeter-wave radar (±1cm accuracy) provide continuous high-frequency monitoring (monitoring frequency increased to 10 times / second), accurately capturing pet location, posture changes, and environmental pollution data, providing a basis for trajectory adjustment and feedback linkage.

[0204] Multimodal feedback synchronization: Auditory: The directional speaker system dynamically emits sound based on the virtual prey's trajectory, and the sound effects are synchronized with the prey's movement (such as running sounds and pause sounds). Tactile: The steerable airflow jet module (0-180° steer) deflects precisely with the prey's trajectory, continuously outputting a gentle airflow that is appropriate for the distance, simulating the wind sensation of the prey running; The energy harvesting module enters the "high-efficiency harvesting + dynamic energy storage" state: The piezoelectric ceramic (conversion efficiency ≥25%) and TENG (output power ≥0.5mW / cm²) energy harvesting device maintain "high sensitivity triggering". The mechanical energy generated by the pet's scratching, running, rubbing against the device can be captured in real time and converted into electrical energy. The supercapacitor energy storage unit (cycle life ≥ 100,000 times) dynamically adjusts the charging and discharging rhythm: when the energy collection is greater than the equipment energy consumption, the excess electrical energy is stored; when the collection is temporarily insufficient, the stored electrical energy is released to supplement it, ensuring that the core module does not stop operating.

[0205] Dynamically adapt operating parameters to balance cleaning efficiency and pet experience: Prioritize pollution areas: Based on real-time pollution data, the system automatically increases the guidance weight of high-pollution areas—the activity frequency and dwell time of virtual prey in high-pollution areas increase, and the intensity of multimodal feedback (sound effects, airflow) in the area is moderately increased (not exceeding the pet's comfort threshold), guiding the pet to focus on cleaning. Pet status adaptation: The pet's status (such as "energetic" or "low interest in exploration") is determined by a posture recognition algorithm (supporting ≥10 action categories). The movement speed (adjustable from 0.4 to 1.2 m / s), trajectory complexity (switching between straight running / zigzag turning / intermittent pauses) and feedback intensity (enhancing sound effects / airflow attraction when interest is low, and increasing trajectory complexity when energy is high) of the virtual prey are also adjusted. Intelligent energy allocation: Core modules (AR projection, directional sound effects, air jet) receive priority energy supply, while non-core functions (such as device indicator light brightness) reduce energy consumption appropriately, ensuring that "energy is used where it is most needed" and avoiding ineffective waste.

[0206] The core of the normal operating mode is "full-function collaboration + dynamic adaptation." It not only activates core modules to meet pet interaction and cleaning needs, but also relies on a self-powered system to achieve energy self-sufficiency, avoiding the drawbacks of traditional devices' "continuous high power consumption." Simultaneously, dynamic parameter adjustments make cleaning guidance more precise and the pet-friendly experience more convenient. Furthermore, it integrates multiple energy harvesting technologies to construct a hybrid energy supply architecture, ensuring stable power supply in different scenarios. Users can view the device's energy self-sufficiency rate and battery life on their mobile phones. These technological effects not only reduce daily standby power consumption but also improve energy self-sufficiency rate and extend device battery life.

[0207] Implementation Example: A cat habitually sharpens its claws near the air purifier in the living room every morning. A piezoelectric ceramic device on the side of the purifier detects the vibrations from the scratching and converts them into electrical energy stored in a supercapacitor. When the cat leaves, the module uses a camera and radar to confirm no activity and automatically switches to a low-power mode, retaining only basic sensing functions. When the cat returns to play in the afternoon, the TENG device collects energy again through the friction from the cat's running. The mobile app shows that the electrical energy collected from the pet's behavior that day met 30% of the device's energy needs, and the remaining supercapacitor power can support 12 hours of standby overnight without external power supply.

[0208] Metaverse Training Extension Platform: The Metaverse training extension platform is equipped with a lightweight VR rendering engine, with a single-frame rendering time controlled within 10ms, ensuring smooth presentation of virtual scenes. Its digital twin modeling tools have a modeling error of no more than 5%, accurately constructing virtual models corresponding to the physical environment and air purifier.

[0209] The platform's edge computing nodes, with a computing power of 5 TOPS or higher, provide robust computational support for the platform's efficient operation. The smart contract platform supports ERC-721 and ERC-1155 protocols, meeting diverse application needs.

[0210] The platform enables integrated virtual and real-world training. Users can log in via their mobile phones to control virtual air purifiers and virtual pets for training. Through digital twin technology, the virtual training results are mapped to physical devices, forming a training system that blends online and offline learning. For example, a virtual pet can be trained to chase virtual prey along a specific route on the virtual platform, and the physical device will then use this training method to guide the real-world pet.

[0211] A value confirmation mechanism has been established, pet behavior data has been digitized into NFTs, and a digital asset circulation ecosystem has been built, allowing users to trade or display these digital assets on the platform. Cross-pet collaborative tasks have been designed, such as multiple pets teaming up to complete virtual purification tasks, forming a community incentive system that enhances user stickiness and participation.

[0212] These technological applications not only enhance user engagement but also improve training efficiency and increase user retention, adding more fun and value to the use of pet air purification systems. Users can view training progress, virtual asset status, and the operational status of physical air purifiers affected by training in real time on their mobile devices.

[0213] Implementation Example: A user creates a virtual avatar for their Golden Retriever on the mobile Metaverse platform and participates in a "Whole House Purification Challenge." A purification route from the living room to the bedroom is planned in the virtual environment, and the virtual Golden Retriever is trained by controlling a virtual purifier to set the prey's movement trajectory. After training, the system synchronizes the route plan to the physical purifier in the home. In reality, the physical purifier immediately projects the prey's trajectory according to the virtual plan, and the Golden Retriever runs along the training route, completing the coverage of all polluted areas in the house. After the event, the platform generates an NFT badge from the Golden Retriever's behavior data, which the user can display in the community. The virtual currency earned can be redeemed for physical pet food coupons.

[0214] In the cleaning system, the core element of "dynamic gamified guidance" is "the system monitors environmental data in real time and intelligently adjusts the cleaning path of virtual prey based on information such as the distribution of polluted areas." This is also the key technological support for accurately transforming pets' "playful behavior" into "cleaning productivity." Through multi-dimensional environmental perception, intelligent algorithm decision-making, and AR projection linkage, this mechanism ensures that pets efficiently cover highly polluted areas while enjoying the chase, completely solving the pain points of traditional purification equipment such as "numerous cleaning blind spots and low efficiency."

[0215] Real-time environmental data monitoring: Building a "dynamic map" of cleaning needs. The system does not rely on fixed cleaning paths, but rather uses multiple sensors to collaboratively collect environmental data and update indoor pollution distribution in real time, providing precise data for adjusting the virtual prey trajectory. Its monitoring system mainly comprises three core dimensions: (I) Monitoring of Pollution Concentration and Type: Identifying Core Cleanliness Objectives The system incorporates a high-precision air quality sensor and a dust detection module, enabling it to capture real-time concentration data of indoor pollutants such as PM2.5, dust particles, pet hair, and food scraps. It then uses algorithms to label pollution levels (e.g., "light pollution," "moderate pollution," "heavy pollution"). For example, when food scraps dropped by pets create a localized high-pollution area on the dining room floor (dust concentration ≥ 0.5 mg / m³), or when long-term dust accumulation under sofas and on top of cabinets causes PM2.5 levels to exceed the indoor average by 30%, the sensor immediately transmits the coordinates, pollution type, and concentration data of that area to the system's main control chip, marking it as a "priority cleaning area."

[0216] Meanwhile, for high-frequency pet activity scenarios (such as under cat trees or around dog kennels), the system will activate a "dynamic sampling mode" to increase the monitoring frequency from the normal frequency to a high frequency, so as to avoid data lag after the spread of pollutants due to pet activities and ensure the timeliness of locating polluted areas.

[0217] (II) Spatial Structure and Obstacle Monitoring: Planning a Safe and Feasible Trajectory: Combining a 1080P high-definition camera with a 60GHz millimeter-wave radar (detection accuracy ±1cm), the system scans the indoor space structure in real time, constructing a "spatial map" that includes furniture positions and obstacle distribution. For example, when it detects that the passageway between the coffee table and TV cabinet in the living room is only 60cm wide, or that the height under the bed in the bedroom is only 15cm, the system will overlay this data with information on contaminated areas, eliminating trajectories that "virtual prey cannot pass through" or "pets are likely to collide with."

[0218] For "stubborn dead corners" that traditional purification equipment can hardly reach, such as under beds, sofa crevices, and cabinet corners, millimeter-wave radar will use penetrating detection to confirm the pollution situation and passable space in the dead corner. If dust is found to be accumulated in a sofa crevic and a pet can enter (width ≥ 10cm), the dead corner will be marked as a "key guidance area" to provide spatial basis for subsequent virtual prey trajectory design.

[0219] (III) Real-time pet location and status monitoring: Efficiency of matching trajectory guidance: While monitoring environmental data, the system uses visual recognition (high-definition camera + image processing chip) in conjunction with millimeter-wave radar to track the pet's location, movement speed, and behavioral state (such as "running fast," "slowly exploring," and "briefly stopping") in real time. For example, when the camera captures a cat slowly pacing in the center of the living room, the system determines that the pet is currently "highly inclined to explore but moving slowly"; if it finds a dog running fast on the balcony, it identifies it as "energetic and driven to chase." This data is simultaneously fed back to the trajectory adjustment algorithm to ensure that the virtual prey's movement speed and route complexity match the pet's state, avoiding situations where the pet abandons the task due to overly difficult trajectories or where overly simple trajectories result in incomplete cleaning coverage.

[0220] Intelligent Adjustment of Virtual Prey Movement Trajectory: From "Blind Guidance" to "Precise Cleaning" Based on real-time collected environmental data, the system uses a built-in "dynamic trajectory algorithm" to adjust the movement trajectory of virtual prey (such as AR-projected "mice" and "butterflies") from three dimensions: "route planning, speed adaptation, and dwell strategy." The core logic is to "prioritize coverage of highly polluted areas, focus on guiding blind spots, and adapt to pet behavior." The specific adjustment strategies are as follows: (a) Priority-based approach based on pollution level: High-pollution areas are given priority coverage. The system will "weight" the virtual prey's trajectory based on the pollution level of the contaminated area—the higher the pollution level, the more frequently the virtual prey will be active and the longer it will stay in that area. For example: When both the living room corner (heavy pollution level) and the balcony (light pollution level) are polluted, the virtual prey will first generate a movement trajectory in the living room corner, attracting the pet to stay by "short-distance back and forth + intermittent stops" (e.g., staying for 2-3 seconds each time, repeating 3-4 times), ensuring that the pet thoroughly cleans the stains in the area by rubbing its body and stepping on it with its paws; after the pollution level in the living room corner drops to "light", the virtual prey will then be guided to move to the balcony, covering the balcony area by "long-distance straight-line running", avoiding wasting the pet's energy in the low-pollution area.

[0221] For multiple scattered areas with slight pollution (such as next to the coffee table in the living room or under the dining table in the dining room), the virtual prey will use a "serialized trajectory" to guide the pet to the areas in order of "pollution concentration from high to low", forming a "closed loop of cleaning path" to avoid the pet running around in different areas and improve cleaning efficiency.

[0222] (II) Targeted guidance for stubborn blind spots: Breaking through cleaning blind areas: For hard-to-clean corners such as under beds and sofa crevices that are difficult to clean with traditional equipment, the system will design a "dedicated trajectory for hard-to-clean corners" to guide pets into these corners for cleaning through "edge guidance + gradual deepening".

[0223] For example, if the area under the bed (1.2m deep, "moderate" contamination level) is a cleaning dead zone, the virtual prey will first project a "small jumping" trajectory at the edge of the bed (close to the pet's current position) to attract the pet's attention; when the pet gets close to the edge of the bed, the virtual prey will gradually move deeper into the bed (moving 10-15cm each time, pausing for 1-2 seconds) to avoid the pet retreating due to "unknown fear" from directly entering the dead zone; after the pet follows into the bed, the virtual prey will make "circular movements" in the dead zone to ensure that the pet fully covers every contaminated area under the bed during the chase.

[0224] For narrow gaps in sofas and cabinets, the virtual prey will adjust to a "slender movement trajectory" (the width matches the gap, about 8-10cm), moving at a "slow crawling" speed to ensure that the pet's paws can reach into the gap to step on and remove dust and food residue.

[0225] (III) "Dynamic Adaptation" to Pet Status: Improving Interaction and Cleaning Efficiency The system adjusts the movement speed and trajectory complexity of the virtual prey based on real-time monitoring of the pet's status, ensuring the pet maintains its interest in chasing while maximizing the cleaning coverage area. When the pet is a "young kitten / puppy" (energetic but with low stamina), the virtual prey will use a "short sprint + frequent pauses" trajectory (speed about 0.5m / s, pausing for 1 second every 1-2 meters) to prevent the pet from getting tired due to chasing too long a distance; if the pet is an "adult dog" (strong stamina and fast speed), the speed of the virtual prey will be increased to 1-1.2m / s, and a complex trajectory of "zigzag running + sudden change of direction" will be designed to fully exhaust the pet's excess energy, while expanding the cleaning coverage area.

[0226] If the system detects a "decline in interest" signal in the pet (such as stopping chasing or turning to other things), it will immediately adjust its trajectory strategy: on the one hand, it will reduce the movement speed of the virtual prey and increase attention-grabbing actions such as "circling in place" or "suddenly appearing"; on the other hand, it will guide the virtual prey to a nearby low-pollution area (such as next to the cat tree where the pet often plays), and re-stimulate the pet's chasing intention through "familiar environment + simple trajectory". After the pet's interest is restored, it will be guided to a high-pollution area.

[0227] The technical support and practical effects of trajectory adjustment achieve a dual improvement in "cleaning efficiency" and "pet experience": To ensure the real-time, accurate, and smooth adjustment of virtual prey trajectories, the system forms a technological closed loop through hardware support and algorithm optimization, ultimately achieving a dual improvement in cleaning effectiveness and pet experience. (I) Technical Support: Low latency and highly smooth trajectory presentation: On the hardware side: The mini AR projection module has a brightness of ≥500 lumens and a refresh rate of 120Hz, so the trajectory of the virtual prey can be clearly seen even in bright daylight. The high refresh rate of 120Hz ensures that there is no lag or ghosting when adjusting the trajectory, avoiding the pet being unable to catch up with the prey due to screen delay, which would affect the interactive experience.

[0228] At the algorithm level: The trajectory adjustment algorithm is mounted on a high-performance processing chip, with a response time of ≤100ms from "receiving environmental data" to "generating a new trajectory". This ensures that the trajectory of the virtual prey can follow the changes in environmental data in real time, and avoids the pet missing highly polluted areas due to adjustment lag.

[0229] (II) Actual Results: Both cleaning coverage and pet participation have been improved. Through a mechanism of "real-time monitoring of environmental data + intelligent trajectory adjustment," the system achieves two major breakthroughs compared to traditional air purifiers: Improved cleaning coverage: Traditional equipment typically achieves less than 60% cleaning coverage due to fixed routes or inability to reach hard-to-reach areas; however, this system, through precise guidance of virtual prey, can increase cleaning coverage to over 90%, with the most significant improvement in cleaning coverage of hard-to-reach areas such as under beds and sofa crevices, solving the core problem of "stubborn hard-to-reach areas not being cleaned".

[0230] Extended pet engagement: Because the trajectory is always adapted to the pet's state and interests, the duration of a single pet interaction is extended from 5-8 minutes in the traditional approach to 15-20 minutes (as in the implementation example, the kitten continued to chase prey for 20 minutes and still maintained its interest). This not only improves the cleaning effect per session, but also fully releases the pet's excess energy and reduces destructive behavior.

[0231] The working principle of capacitive sensing technology: When a pet approaches the device surface, the sensing electrodes pre-placed on the surface and the capacitive sensing circuit work together to create an electric field environment. The pet's body, rich in water and other conductive substances, can be considered a conductor. Once the pet enters the sensing range of this electric field, it disrupts the original electric field balance, causing a change in the electric field distribution around the touch point. This change, in turn, leads to a change in the capacitance value at that location. Specifically, the pet's approach creates a new capacitive coupling path, connecting in parallel with the existing capacitive system, thus increasing the total capacitance.

[0232] The capacitive sensing circuit continuously monitors changes in capacitance between the sensing electrode and ground. Once a change in capacitance is detected, the voltage or charge in the capacitive sensing circuit changes accordingly. These changes are quickly captured and converted into electrical signals. These signals are then transmitted to the system's control module, where a dedicated signal processor analyzes the patterns and characteristics of the capacitance changes to accurately determine whether a pet is approaching and its approximate location, providing crucial information for subsequent device responses.

[0233] Practical Application Example: In daily life, capacitive sensing technology has a wide range of practical applications in pet air purification systems. When a pet roams freely in a room and approaches an air purifier placed in a corner, the capacitive sensing technology comes into play. For example, a cat chasing a toy gradually approaches the purifier. At this moment, the capacitive sensor on the purifier's surface quickly detects the cat's approach. The internal circuitry detects the change in capacitance and converts it into an electrical signal, which is then transmitted to the control chip. Upon receiving the signal, the control chip immediately reacts, such as initiating the device's initial preparation program and adjusting the internal purification components to a standby state, ready to respond further based on the pet's subsequent behavior. Meanwhile, to allow owners to intuitively understand the interaction between their pet and the device, the device will also provide some external prompts. For example, the indicator light on the top of the device will change from its usual standby state to a flashing state, using a soft light change to attract the owner's attention and inform them that their pet has approached the device, and an interesting interaction may be about to begin. Alternatively, the mobile app connected to the device will also push notification messages, displaying messages such as "Your pet has approached the air purifier, an exciting interaction is about to begin," allowing owners who are not at home to know the real-time status of their pet and the device, increasing the fun and interactivity of pet ownership.

[0234] Light trajectory recognition technology: This technology can keenly capture subtle movements when a pet touches a device and deeply analyze the underlying behavioral intentions. Its core components include a 1080P high-definition camera, an image processing chip, and a series of complex and sophisticated algorithms. These components work together to form a highly efficient motion capture and analysis system. When a pet lightly touches the device surface with its paws, nose, or other parts, the high-definition camera quickly activates, rapidly capturing continuous footage of the pet's movements at a frame rate of tens or even higher per second. This image data is then quickly transmitted to the image processing chip, where it begins comprehensive processing and analysis. During the analysis, the algorithm precisely tracks the pet's movements. It identifies the starting point, path, and ending point of each touch, recording and analyzing this key location information to depict the complete trajectory of the pet's actions. For example, if the pet scratches the surface of a device with its paw, the algorithm can accurately identify features such as the direction, length, and arc of the scratch. Simultaneously, the algorithm calculates the speed of the movement, determining whether the pet is touching slowly and gently or slapping quickly and forcefully, which helps to further understand the pet's behavioral state and emotions. Force analysis is also a crucial aspect of light trajectory recognition technology. By comprehensively considering factors such as the degree of deformation, contact area, and acceleration of the movement at the point where the pet touches the device in the image, the algorithm can estimate the force of the pet's action. For example, when the pet lightly touches the device, the contact area shown in the image is small, and the degree of deformation is not obvious, so the algorithm judges the force as light; while when the pet forcefully hits the device, the contact area increases, and there may be a brief blur (due to the rapid movement), so the algorithm can identify a greater force. By comprehensively analyzing multi-dimensional features such as movement trajectory, speed, and force, the system can accurately identify the pet's behavioral intentions. If the pet taps the device surface rapidly and repeatedly, it may mean it wants to quickly activate a function or start a game; if the pet slowly swipes across the device surface, it may be exploring the device's functions or simply making random movements out of curiosity. This behavior intention recognition method based on multi-feature analysis greatly improves the accuracy and intelligence of the system's interaction with the pet, enabling the device to respond appropriately based on the pet's true intentions.

[0235] Real-world application examples: In daily pet ownership, light trajectory recognition technology has a wide variety of practical applications, bringing convenience and enjoyment to both pets and their owners. For instance, when a playful cat is playing at home, it might accidentally discover an air purifier placed nearby. Curious, the cat walks over and gently taps the device's surface with its paw. At that moment, the device's high-definition camera quickly captures this action, and the light trajectory recognition technology is immediately activated. By analyzing the trajectory, speed, and force of the cat's clicking actions, the system accurately determines that the cat intends to interact. The device then responds accordingly: the AR projection module projects a virtual mouse onto the ground, and simultaneously, the mouse's squeaking sound comes from the device's built-in speaker. The cat, triggered by this scene, begins to chase the virtual mouse. During the chase, the cat repeatedly touches the mouse with its paws, and each touch is precisely captured by the light trajectory recognition technology. If the cat clicks rapidly and continuously, the system interprets this as the cat being excited and increases the mouse's movement speed, increasing the game's difficulty and fun; if the cat's movements slow down, the system appropriately reduces the mouse's movement speed, making it easier for the cat to catch and maintaining its engagement. For example, a small dog approaches an air purifier and rubs its nose against the device's surface. Light trajectory recognition technology quickly captures the dog's movements. After analysis, the system determines that the dog may be looking for information or seeking attention. At this point, the device projects images of the dog's favorite foods or plays a recording of the owner's voice. The dog, seeing and hearing these things, appears very happy and continues to interact with the device. The owner can also monitor the dog's interaction with the device in real time via a mobile app, experiencing their pet's joy even when not at home. This precise interaction based on light trajectory recognition technology not only allows pets to enjoy themselves but also helps owners better understand their pets' needs and emotions, significantly improving the quality of pet ownership.

[0236] The interactive pet purification system employs a dual-technology collaborative mechanism: capacitive sensing technology and light trajectory recognition technology work closely together to build a highly efficient and accurate interactive system. When a pet roams freely in the room, capacitive sensing technology, with its keen electric field perception capabilities, can quickly detect subtle changes in the electric field once the pet approaches the device surface. This allows for accurate judgment of the pet's approach and timely transmission of this information to the system's core processing unit. As the pet approaches and lightly touches the device's surface, a high-definition camera rapidly captures the instantaneous moment of the pet's touch at an extremely high frame rate. The image processing chip immediately performs a comprehensive and in-depth analysis of these images. It identifies the starting position of the pet's touch and the trajectory of the movement. Simultaneously, by comprehensively considering factors such as the degree of deformation of the part of the device the pet is in contact with, and the duration of contact, the system can accurately determine the force of the pet's movement. The system analyzes motion characteristics using light trajectory recognition technology and combines this with a pre-set behavior pattern library to accurately identify the pet's behavioral intentions. For example, if the pet taps the device surface rapidly, the system determines it may want to quickly activate a function or start a fun game; if the pet slowly swipes across the surface, the system infers it may be curiously exploring the device's functions or simply acting out of boredom. Based on this accurate behavioral intention recognition, the system quickly responds accordingly. If it determines the pet wants to start a game, the system immediately activates the AR projection module, projecting a virtual prey onto the ground, while simultaneously playing realistic prey sounds through built-in speakers to stimulate the pet's hunting instincts; if it determines the pet is exploring functions, the system uses AR projection to display relevant function introductions and operation guides, guiding the pet to further understand and use the device. This complete interactive process, from capacitive sensing to light trajectory recognition, to behavioral intention judgment and system response, is seamless.

[0237] Compared to traditional air purifier interaction technologies, the combination of capacitive sensing and light trajectory recognition technologies offers numerous significant advantages. In terms of accuracy, traditional devices can only react to pressure applied by a pet in a specific area, often failing to detect or recognize subtle movements or indirect pressure contact around the device. Capacitive sensing technology, however, can sensitively detect a pet's approach, while light trajectory recognition technology can precisely capture the subtle movement characteristics of a pet touching the device, analyzing movement trajectory, speed, and force from multiple dimensions, greatly improving the accuracy of recognizing the pet's intentions. For example, traditional devices may fail to distinguish between unintentional approach and intentional interaction, while the dual-technology system can accurately determine the pet's true intentions through precise analysis and respond appropriately.

[0238] From a durability perspective, traditional devices, due to frequent physical pressure during long-term use, are prone to problems such as button wear, poor contact, and decreased sensor sensitivity. This not only affects the normal operation of the device but also increases maintenance costs and replacement frequency. Capacitive sensing and light trajectory recognition technologies use non-contact interaction methods, avoiding physical damage caused by direct contact between pets and the device, greatly reducing the risk of damage and extending the device's lifespan. For example, capacitive sensing technology detects a pet's approach through changes in the electric field, eliminating the need for physical contact; light trajectory recognition technology relies on camera-captured images for analysis, avoiding the wear and tear of mechanical parts, allowing the device to operate more stably and for longer. In terms of the richness of interactive experience, traditional interaction methods are limited to simple pressure-sensitive operations, resulting in a monotonous interaction style that fails to stimulate a pet's interest and curiosity, leading to a low frequency of interaction between the pet and the device. The dual-technology system, however, brings a completely new interactive experience to pets. When a pet approaches the device, it triggers a series of fun interactive activities. From the virtual scenes and prey displayed by AR projection, to the various sound effects played by the built-in speakers, and the real-time feedback from the system based on the pet's behavior, such as adjusting the movement trajectory of the virtual prey, it comprehensively stimulates the pet's vision, hearing, and touch, creating a fun and attractive interactive environment that greatly enhances the pet's enthusiasm and engagement in the interaction. This rich and diverse interactive experience allows pets to gain more enjoyment from interacting with the device, and also allows owners to better observe and understand their pets' behavior and emotions.

[0239] This application also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, it implements the above-described pet-based cleaning method.

[0240] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described pet-based cleaning method.

[0241] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0242] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0243] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0244] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0245] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0246] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0247] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0248] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0249] The above provides a detailed description of the pet-based cleaning method, cleaning system, electronic device, and storage medium. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A pet-based cleaning method, characterized in that, Applied to a cleaning system, the method includes: When a cleaning event is triggered in the environment targeted by the cleaning system, a cleaning path is determined for that environment; Guide the pet to move along the cleaning path to clean the environment.

2. The method according to claim 1, characterized in that, The method further includes: Data is collected from the pet to obtain target sensor data; Based on the target sensing data, determine the pet's emotional intention; When the emotional intent is an interactive intent, a cleaning event is determined that triggers the cleaning system for the environment in which it targets.

3. The method according to claim 2, characterized in that, The cleaning system includes at least one of the following sensors: Capacitive sensors, light field touch sensors, image acquisition sensors, and sound acquisition sensors; The target sensing data includes at least one of the following: Capacitance change data, light trajectory data, light intensity change data, image data, and audio data.

4. The method according to claim 1, characterized in that, The method further includes: Obtain pollution status information of the environment; Based on the pollution status information, determine whether to trigger a cleaning event for the environment targeted by the cleaning system.

5. The method according to claim 4, characterized in that, Determining the cleaning path for the environment includes: Based on the pollution status information, determine the pollution level information of each area in the environment; The cleaning path is generated based on the pollution level information.

6. The method according to claim 1, characterized in that, Guiding the pet to move along the cleaning path includes: Determine the target projection image; The target projection image is projected along the cleaning path.

7. The method according to claim 6, characterized in that, When projecting the target projection image along the cleaning path, the method further includes: Play target audio data corresponding to the target projected image at the current projection position of the target projected image; and / or, Airflow is directed to the current projection position of the target image.

8. A cleaning system, characterized in that, The application includes a pet-based cleaning method as described in any one of claims 1-7, the cleaning system comprising: The target sensing module is used to collect sensing data on the environment targeted by the cleaning system. The control module is used to determine whether a cleaning event for the environment targeted by the cleaning system is triggered based on the sensor data; when a cleaning event for the environment targeted by the cleaning system is triggered, it determines a cleaning path for the environment; and guides the pet to move along the cleaning path to clean the environment. A guidance module is used to guide the pet to move along the cleaning path in order to clean the environment.

9. The cleaning system according to claim 8, characterized in that, The target sensing module includes at least one of the following: A capacitive sensor is used to sense changes in an electric field and output capacitance change data. A light field touch sensor includes a quantum dot fluorescent coating, a light source unit, and a light acquisition module; the light source unit is used to emit excitation light to the quantum dot fluorescent coating. The light acquisition module is used to acquire the excitation light received on the quantum dot fluorescent coating to obtain light trajectory data and / or light intensity change data; An image acquisition sensor is used to acquire images of the environment and output image data; A sound acquisition sensor is used to acquire sound from the environment and output audio data.

10. The cleaning system according to claim 8, characterized in that, The guidance module includes: The projection unit is used to project a target image along the cleaning path.

11. The cleaning system according to claim 10, characterized in that, The guidance module also includes at least one of the following units: An audio playback unit is used to play target audio data corresponding to the target projection image at the current projection position of the target projection image; The airflow projection unit is used to directionally project airflow at the current projection position of the target projection image.

12. The cleaning system according to claim 8, characterized in that, The cleaning system also includes: An energy harvesting module is used to convert the pet's kinetic energy into electrical energy and supply it to the cleaning system.

13. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the pet-based cleaning method as described in any one of claims 1 to 7.

14. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the pet-based cleaning method as described in any one of claims 1 to 7.

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