A pet care air purifier parameter intelligent control method and system

Abstract

The application discloses a pet care air purifier parameter intelligent control method and system, aiming at solving the problem that the existing purifier is difficult to identify the long-time stillness of pets in the monitoring blind area, resulting in the accumulation of local pollution. The method continuously receives the data stream of the visual sensor and the passive infrared sensor, and when no clear pet signal is detected within the preset time, the blind area intention inference instruction is activated, the multi-dimensional environmental abnormal signal of odor, local temperature and particulate matter is collected, and after time consistency, space correlation and comprehensive threshold correlation analysis, the adaptive purification strategy of fan speed fine tuning, filter optimization and directional airflow guidance is executed after the pet in the blind area is confirmed to be still. According to the recovery of pet activity or the weakening of environmental abnormalities, the method can be switched to the normal mode or the low-power mode. The application can accurately identify the still state of the pet in the blind area, remove the pollutants in a targeted manner, balance the purification efficiency, energy saving and low noise, and improve the fine management level of indoor air quality.

Description

Technical Field

[0001] This invention relates to the field of pet care air purifier technology, and more particularly to an intelligent control method and system based on parameters of a pet care air purifier. Background Technology

[0002] As pets play an increasingly important role in modern families, the demand for sophisticated indoor air quality management continues to rise. Smart air purifiers, as a core solution, integrate multiple environmental sensing units, including visual sensors, passive infrared sensors, and odor sensors. They comprehensively analyze pet activity data and dynamically adjust parameters such as fan speed, filter mode, and directional airflow to ensure indoor air quality meets standards while achieving an optimal balance between energy consumption and noise. Their core design logic is based on training pets' typical behavioral patterns in common areas such as the ground and low furniture, allowing them to effectively balance purification performance and energy efficiency in traditional home layouts and pet activity scenarios.

[0003] However, as pets become more familiar with their home environment, their behavioral patterns gradually become more diverse. Felines, in particular, driven by their exploratory instincts, need for security, and preference for heights, will actively use vertical spaces in the home (such as tall bookshelves or ceiling-high pet trees) and secluded corners (such as the gap between the sofa and the wall) as new resting or observation points. These emerging activity areas often exceed the initial design scope of air purifiers, and due to their unique spatial locations, they are highly susceptible to becoming blind spots or signal blockage areas for sensors, making it difficult for existing purification systems to adapt.

[0004] In these atypical areas, visual sensors face significant challenges. Cameras installed low on air purifiers may fail to capture complete images of pets due to limited viewing angles and obstructions. Even if some pets are visible, insufficient image resolution may result from tilted shooting angles, excessive distance, or inadequate lighting, making it difficult to extract key identification information such as pet species and posture. Ultimately, the algorithm may misjudge the pets as background clutter or invalid data.

[0005] The problems with passive infrared sensors are even more pronounced. These sensors rely on detecting the thermal radiation of living organisms to determine the presence and movement of pets. When a pet is in a hidden corner or completely blocked by heavy curtains or furniture, the infrared signal it emits will be absorbed, reflected, or scattered by the obstacles, causing the signal strength to decrease sharply and fall below the system's recognition threshold, making it impossible to effectively detect the presence of a pet. Even if the signal does not completely disappear, the complex reflection and refraction can make the signal characteristics abnormal. Weak and intermittent signals are easily misinterpreted as ambient temperature fluctuations or sensor noise, rather than real pet signals.

[0006] The lack of robustness in the core judgment logic further exacerbates the problem. The existing system's recognition algorithm is mainly trained on clear, typical pet activity data, and lacks effective processing capabilities when faced with incomplete, weakened, and low-quality sensor data. For example, sporadic and weak infrared signals may be misjudged as "pet briefly passing by" or "no pet activity," and blurry local images cannot be distinguished from background clutter, ultimately leading the system to make the incorrect judgment of "no pet activity."

[0007] Misjudgment directly leads to unreasonable adjustments in the purification strategy. To conserve energy, the system may maintain low power consumption or standby mode, with the fan running at a low speed and some advanced filter functions suspended. This leaves it unable to handle pollutants such as dander, hair, saliva particles, and volatile organic compounds (VOCs) continuously generated by pets staying in blind spots for extended periods. These pollutants gradually accumulate in localized areas, causing a significant increase in PM2.5, PM10, and VOC concentrations, exceeding not only home comfort standards but also potentially posing a respiratory health threat to sensitive individuals.

[0008] While users expect air purifiers to achieve "whole-house cleanliness," existing systems fail to recognize prolonged periods of inactivity by pets in atypical areas, resulting in inefficient operation and continuous deterioration of localized air quality. This phenomenon highlights a core limitation of current intelligent control methods: given the diverse behavioral patterns of pets and the complex spatial environment of the home, their ability to monitor and continuously purify atypical activity areas is severely inadequate, making it difficult to meet the comprehensive and refined air quality management needs of families. Summary of the Invention

[0009] The purpose of this invention is to propose an intelligent control method for pet care air purifier parameters, which aims to solve the problem that existing intelligent air purifiers cannot effectively identify and adjust their purification strategies when pets remain stationary in the monitoring blind zone for a long time, thus causing a decline in air quality in local areas.

[0010] This invention is implemented as follows: a method for intelligent control of parameters of a pet care air purifier, the method comprising the following steps: It continuously receives data streams from the visual sensor and the passive infrared sensor. When no pet image features are identified within a preset time or only intermittent signals below the first voltage threshold are detected, it sends an activation blind zone presence inference command. Initiate multi-dimensional environmental anomaly signal acquisition, including data acquisition from odor sensors, local ambient temperature sensors, and particulate matter sensors; Correlation analysis was performed on the collected multidimensional environmental anomaly signals to infer the intention of the pet to remain stationary for a long time in the monitoring blind zone; When it is confirmed that the pet intends to remain stationary for an extended period within the monitoring blind spot, an adaptive purification strategy is adjusted.

[0011] Furthermore, the method also includes continuous monitoring and mode switching steps: When the visual or passive infrared sensor detects a clear pet activity signal again, switch back to the regular pet activity mode; When the multidimensional environmental anomaly signal continues to weaken and falls below the judgment threshold within a preset time, switch back to low power mode.

[0012] Furthermore, the odor sensor, local ambient temperature sensor, and particulate matter sensor respectively collect data on the concentration of volatile organic compounds or ammonia in the air, local area and background temperature data, and PM2.5 and PM10 concentration data, and monitor the slight upward trend of each indicator relative to the benchmark value.

[0013] Furthermore, the association analysis includes: Time consistency assessment: Check whether each abnormal signal remains stable or continues to rise within a preset time period; Spatial correlation assessment: Analyze whether data from multiple sensors are concentrated in a specific direction or adjacent areas; Comprehensive threshold judgment: At least two abnormal signals simultaneously meet the time consistency requirement, and their intensity is lower than the conventional pollution trigger threshold.

[0014] Furthermore, the logical expression for confirming the intention of the pet remaining still for an extended period within the monitoring blind zone is as follows: Intent confirmation = ((Volatile organic compound increase AND ammonia increase) OR (Local temperature increase) OR (PM2.5 increase AND PM10 increase)) AND (At least two signals meet time consistency) AND (The strength of all signals meeting the conditions is below the normal trigger threshold).

[0015] Furthermore, the adaptive purification strategy adjustment includes fine-tuning of fan speed, optimization of filter function, and directional airflow guidance.

[0016] Furthermore, the odor sensor employs a highly sensitive semiconductor gas sensor; The local ambient temperature sensor employs at least two high-precision digital temperature sensors to monitor a stable temperature difference of 0.5-2 degrees Celsius between the local temperature and the background temperature. The particulate matter sensor is a laser scattering sensor.

[0017] Furthermore, the fan speed is fine-tuned to increase the fan speed to 800-1200 RPM, while keeping the noise level below 30 dB; The filter function optimization includes activating or enhancing the adsorption function of an activated carbon filter with adjustable adsorption efficiency, or increasing the airflow through the filter by increasing the fan speed. The directional airflow guidance is achieved by controlling the airflow louvers or rotating air outlets via a stepper motor or servo motor, and fine-tuning the airflow direction to the direction of the inferred blind spot where the pet is located.

[0018] Another objective of this invention is to provide an intelligent control system for an air purifier based on pet care, the system comprising: The main sensing units include a visual sensor and a passive infrared sensor, used to collect direct signals of pet activity; The main control unit is used to continuously receive data streams from the visual sensor and the passive infrared sensor. When the visual sensor fails to recognize pet image features or the passive infrared sensor only detects intermittent signals below the first voltage threshold within a preset time, it sends an instruction to activate the blind zone intention inference module; at the same time, it sends an instruction to start the multi-dimensional environmental abnormal signal acquisition unit. The multidimensional environmental anomaly signal acquisition unit includes an odor sensor, a local ambient temperature sensor, and a particulate matter sensor, which are used to acquire multidimensional environmental anomaly signals. The odor sensor, local ambient temperature sensor, and particulate matter sensor respectively acquire data on the concentration of volatile organic compounds or ammonia in the air, local area and background temperature data, and PM2.5 and PM10 concentration data. The blind zone presence intent inference module, integrated into the main control unit or independent coprocessor, is used to perform correlation analysis on the received multi-dimensional environmental anomaly signals and infer whether the pet has been stationary in the monitoring blind zone for a long time. An adaptive purification strategy adjustment unit is used to adjust the air purifier's operating parameters when the intent inference unit infers that the pet intends to remain stationary in the monitoring blind zone for an extended period of time. The adjustment of the air purifier's operating parameters includes adjusting the fan speed, optimizing the filter function, and guiding directional airflow.

[0019] Furthermore, the system also includes: The monitoring and mode switching module is used to switch back to the normal pet activity mode when the visual or passive infrared sensor detects a clear pet activity signal again; and to switch back to the low power mode when the multidimensional environmental abnormal signal continues to weaken and falls below the judgment threshold within a preset time.

[0020] Beneficial effects of the present invention This invention discloses an intelligent control method and system for pet care air purifier parameters. The method continuously receives data streams from a visual sensor and a passive infrared sensor. When no pet image features are detected within a preset time or only intermittent signals below a first voltage threshold are detected, an activation command to infer the presence of an intent to enter the blind zone is sent. Subsequently, multi-dimensional environmental anomaly signal acquisition is initiated, including data from an odor sensor, a local ambient temperature sensor, and a particulate matter sensor. Next, correlation analysis is performed on the acquired multi-dimensional environmental anomaly signals to infer the pet's intention to remain stationary for an extended period within the monitoring blind zone. When the pet's intention to remain stationary for an extended period within the monitoring blind zone is confirmed, an adaptive purification strategy is adjusted. This application effectively solves the problem that existing intelligent air purifiers are significantly insufficient in their continuous purification capabilities in atypical activity areas when faced with diverse pet behavior patterns and complex environmental spaces. The method of this invention can accurately identify the prolonged stationary presence of a pet within the monitoring blind zone and dynamically adjust purification parameters accordingly, thereby significantly improving the air quality in the local area and providing a healthier and more comfortable living environment for family members. Attached Figure Description

[0021] Figure 1 This is a flowchart of a preferred embodiment of the present invention for an intelligent control method of parameters of a pet care air purifier; Figure 2 This is a structural diagram of a smart control system based on parameters of a pet care air purifier, according to a preferred embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. For ease of explanation, only the parts related to the embodiments of this invention are shown. It should be understood that the specific embodiments described herein are merely for explaining this invention and are not intended to limit this invention.

[0023] Traditional smart air purifiers primarily rely on training and optimizing common pet behavior patterns on the ground or in low furniture areas for pet activity recognition. However, when pets explore and utilize vertical spaces or hidden corners in the home as new resting or observation points, these areas are often blind spots or signal-blocked locations for the purifier's sensors. This means that visual sensors may fail to capture a complete image or effective features of the pet due to limited viewing angles, obstructions, or insufficient light, while passive infrared sensors may experience a sharp decrease in signal strength due to physical obstacles, thus failing to effectively detect the pet's presence. When receiving incomplete, weakened, or abnormal sensor data, the core judgment logic of existing pet activity recognition systems malfunctions, leading the system to misjudge "no pet activity" or "pet briefly passing by," thereby incorrectly maintaining a low-power operating mode or standby mode and failing to promptly increase purification parameters, resulting in persistently poor air quality in areas where pets spend extended periods. To address this, this application proposes a smart control method for pet care air purifier parameters, which includes the following steps: S1. Continuously receive data streams from the visual sensor and the passive infrared sensor. When no pet image features are detected within a preset time or only intermittent signals below a first voltage threshold are detected, send an activation command to infer the presence of the pet in the blind zone. S2. Initiate multi-dimensional environmental anomaly signal acquisition, including data acquisition from the odor sensor, local ambient temperature sensor, and particulate matter sensor. S3. Perform correlation analysis on the acquired multi-dimensional environmental anomaly signals to infer the pet's intention to remain stationary in the monitoring blind zone for an extended period. S4. When the intention of the pet to remain stationary in the monitoring blind zone for an extended period is confirmed, adjust the adaptive purification strategy. In this embodiment, the blind zone presence intention inference command is a further detection command issued by the system to relevant modules when it initially determines that the pet may be in the monitoring blind zone. In this embodiment, the visual sensor can be, for example, a CMOS image sensor or a CCD image sensor, to identify pet image features by capturing environmental images. The passive infrared sensor can be a pyroelectric infrared sensor, which determines the presence of the pet by detecting infrared radiation emitted by its body. If the visual sensor fails to recognize pet image features within a preset time, for example, due to the pet being obscured by furniture, at a high position, or in insufficient light, the visual sensor may be unable to capture a clear pet image, or the image recognition algorithm may fail to match the preset pet feature model. Simultaneously, the passive infrared sensor may only detect intermittent signals below a first voltage threshold. For example, the pet may be in the edge area of ​​the passive infrared sensor or have slight physical obstruction, resulting in an infrared signal intensity insufficient to reach the conventional recognition threshold, but not completely absent. In this case, the system sends an activation blind zone presence inference command. In this embodiment of the invention, upon receiving the activation blind zone presence inference command, the system initiates multi-dimensional environmental anomaly signal acquisition. This includes data acquisition from the odor sensor, local ambient temperature sensor, and particulate matter sensor. The odor sensor can be a semiconductor gas sensor to detect volatile organic compounds (VOCs) or ammonia and other odor molecules that pets may produce in the air. The local ambient temperature sensor can be a thermistor or an infrared temperature sensor to monitor temperature changes in a specific area to capture potential local temperature increases caused by prolonged pet stays. The particulate matter sensor can be a laser scattering sensor to detect the concentration of PM2.5 and PM10 particles in the air, which may originate from pet dander, hair, etc. In this embodiment of the invention, correlation analysis can employ various data processing and pattern recognition techniques. For example, the system can analyze the temporal trends of odor concentration, local temperature, and particulate matter concentration to determine whether these abnormal signals are consistently stable or gradually increasing. Simultaneously, it can also analyze the spatial distribution of these abnormal signals; for example, whether data from multiple sensors are concentrated in a specific direction or adjacent area to locate potential blind spots for pets.Furthermore, correlation analysis also comprehensively assesses the intensity of these abnormal signals. For example, when at least two abnormal signals simultaneously meet temporal consistency and their intensity is below the conventional pollution trigger threshold, it can be preliminarily determined that the pet may have been stationary in the blind spot for an extended period. In this embodiment of the invention, adaptive purification strategy adjustment may include fine-tuning of fan speed, optimization of filter function, and directional airflow guidance. For example, the system can fine-tune the fan speed based on the inferred pet location and pollutant concentration to increase air circulation and purification efficiency. Simultaneously, filter function can be optimized; for example, the adsorption function of activated carbon filters can be activated or enhanced to more effectively remove odors. Furthermore, directional airflow guidance can precisely deliver purified air to the blind spot where the pet is located, or more effectively guide pollutants within the blind spot to the purifier, thereby achieving precise purification of a localized area.

[0024] In some embodiments described above, this application proposes an adaptive purification strategy adjustment scheme when a pet remains stationary for an extended period within a monitoring blind zone. However, in practical applications, if the system only focuses on the presence of the pet within the blind zone and adjusts the purification accordingly, without a response mechanism for when the pet's state recovers or environmental anomalies are eliminated, the purifier may continue to operate in high-power mode even after the pet has left or the environment has returned to normal, resulting in unnecessary energy waste and potentially impacting user experience. To address this, this application further proposes that the method also include continuous monitoring and mode switching steps: when a visual or passive infrared sensor detects a clear pet activity signal again, the system switches back to the regular pet activity mode; when a multidimensional environmental anomaly signal continuously weakens and falls below a preset threshold within a certain time, the system switches back to the low-power mode. Specifically, the continuous monitoring and mode switching steps aim to ensure that the air purifier system can dynamically adjust its operating mode based on changes in the pet's activity state and environmental anomaly signals. Here, "clear pet activity signal" can be understood as the visual sensor capturing obvious image features such as pet movement and posture changes, or the passive infrared sensor detecting a continuous signal with an intensity higher than a first voltage threshold, indicating that the pet has recovered from its stationary state or the blind zone. When such signals are detected, the system will switch from the adaptive purification strategy adjustment mode for pets in blind spots back to the "normal pet activity mode." This mode typically purifies the air based on preset pet activity patterns or user-defined settings. For example, it maintains a medium fan speed when pets are active to handle pet hair and dander. Furthermore, "multi-dimensional environmental anomaly signals continuously weaken and fall below the judgment threshold within a preset time" means that the abnormal signals (such as volatile organic compounds, ammonia concentration, local temperature increase, PM2.5 and PM10 concentrations) collected by the odor sensor, local ambient temperature sensor, and particulate matter sensor show a decreasing trend over a period of time, and their intensity is all below the preset judgment threshold. This indicates that the local environmental anomalies caused by the pet's prolonged stillness in the blind spot have been effectively alleviated or eliminated. In this case, the system will switch to "low power mode," which aims to minimize energy consumption. For example, the fan speed is reduced to a minimum, or only periodic monitoring is performed to maintain basic air quality while saving energy for the user. Through the above technical solution, this application enables the air purifier system to adjust its operating mode promptly and intelligently after confirming that the pet has left the monitoring blind zone or that abnormal environmental signals have subsided. This not only significantly improves the system's energy efficiency and avoids unnecessary power consumption, but also optimizes the user experience, ensuring that the purifier can provide appropriate and economical purification services in different scenarios.

[0025] In some preferred embodiments, it is assumed that the air purifier system has confirmed, using the method described above, that the pet has remained stationary in the monitoring blind zone for an extended period and has initiated adaptive purification strategy adjustments, such as increasing fan speed and activating the activated carbon filter. Scenario 1: The pet leaves the blind zone and begins to move freely in the room. At this time, the visual sensor recaptures an image sequence of the pet's movement, or the passive infrared sensor detects a continuous and high-intensity movement signal. Upon receiving these clear pet activity signals, the main control unit determines that the pet has returned to normal activity and then sends a command to switch the air purifier back to the preset "normal pet activity mode." In this mode, the fan speed may be adjusted to a medium level to handle the hair and dander generated by the pet's daily activities, while maintaining a low noise level. Scenario 2: After the pet has remained stationary in the blind zone for a period of time, although its activity is not directly detected by the visual or passive infrared sensors, the abnormal local environmental signals it generates (such as odor, temperature, and particulate matter) continue to weaken after the purifier has been running for a period of time. For example, the ammonia concentration detected by the odor sensor drops from 0.5 ppm to below 0.1 ppm, and the temperature difference detected by the local ambient temperature sensor drops from 1.5 degrees Celsius to below 0.3 degrees Celsius, and these signals remain below the preset judgment threshold for 10 consecutive minutes. The main control unit continuously monitors and determines that these multi-dimensional environmental anomalies have been effectively controlled or eliminated, and then sends a command to switch the air purifier to "low-power mode." In this mode, the fan speed may be reduced to a minimum of 300 RPM, maintaining only basic air circulation and monitoring functions to achieve energy-saving operation. In this embodiment of the invention, the odor sensor, local ambient temperature sensor, and particulate matter sensor respectively collect data on the concentration of volatile organic compounds (VOCs) or ammonia in the air, local area and background temperature data, and PM2.5 and PM10 concentration data, and monitor the slight upward trend of each indicator relative to the baseline value. The odor sensor is configured to collect data on the concentration of volatile organic compounds (VOCs) or ammonia in the air. These gases are biological metabolic products that may be produced when pets remain stationary for extended periods, such as pet excrement or body odor. A local ambient temperature sensor is configured to collect temperature data of a local area and the background. Its purpose is to identify the heat emitted by the pet's body by comparing the temperature difference between the local area and the surrounding environment. A particulate matter sensor is configured to collect PM2.5 and PM10 concentration data. These particles may originate from pet hair, dander, or dust mites, and are indirect evidence of the pet's presence. Furthermore, all of the above sensors are configured to monitor the slight upward trend of each indicator relative to a preset baseline value, rather than simply detecting when a certain absolute threshold is reached. By monitoring these slight upward trends, rather than relying on high-intensity signals, subtle changes that occur when a pet remains stationary for extended periods in a blind spot can be effectively identified, thus avoiding missed detections due to insufficient signal strength.Specifically, the aforementioned correlation analysis includes: temporal consistency judgment: checking whether each abnormal signal remains stable or shows a continuous upward trend within a preset time period; spatial correlation judgment: analyzing whether data from multiple sensors are concentrated in a specific direction or adjacent areas; and comprehensive threshold judgment: at least two abnormal signals simultaneously meet temporal consistency, and their intensity is lower than the conventional pollution trigger threshold. The temporal consistency judgment aims to determine whether these signals exhibit a non-random, continuous pattern of change over a period of time by continuously monitoring data collected by odor sensors, local ambient temperature sensors, and particulate matter sensors. For example, if the concentration of volatile organic compounds or ammonia in the air, local area temperature data compared to background temperature data, or PM2.5 and PM10 concentration data show a continuous and slow increase over several minutes, then temporal consistency can be considered met. Its purpose is to filter out instantaneous fluctuations or sporadic events, ensuring that the monitored abnormal signals are continuous, which is consistent with the characteristic of pets remaining still for extended periods. Furthermore, the spatial correlation judgment assesses whether the abnormal signal originates from a local and specific area, rather than a general change in the entire environment, by comparing data from different sensors (e.g., multiple local ambient temperature sensors or odor sensors distributed in different locations). For example, if a local temperature sensor in one direction shows an increase in temperature, while sensors in other directions show no significant change, it indicates that the source of the anomaly may be located in that specific direction. The aim is to narrow down the scope of the anomaly source, focusing attention on a specific blind spot where a pet might be present, thus avoiding misjudgment of general environmental changes. Furthermore, the comprehensive threshold judgment aims to ensure that at least two anomalous signals simultaneously meet temporal consistency and are below the conventional pollution trigger threshold. This judgment aims to avoid misjudgment, i.e., inferring the presence of a pet based solely on a single weak signal or a signal with an intensity reaching conventional pollution levels. For example, when the concentration of volatile organic compounds and the local temperature simultaneously show a weak but continuous upward trend, and these increases are insufficient to trigger the high-intensity operation mode of a conventional air purifier, the comprehensive threshold judgment is met. Its purpose is to improve the accuracy and reliability of inferring the intention of a pet to remain stationary for an extended period within the monitoring blind spot without triggering excessive purification. Specifically, in some implementations, the confirmation of a pet's intention to remain stationary for an extended period within the monitoring blind spot is achieved through the following logical expression. The logical expression for confirming the intention of a pet remaining stationary for an extended period within the monitoring blind zone is: Intention Confirmation = ((Volatile Organic Compounds Rise AND Ammonia Rise) OR (Local Temperature Rise) OR (PM2.5 Rise AND PM10 Rise)) AND (At least two signals meet the time consistency) AND (The strength of all signals meeting the conditions is lower than the conventional trigger threshold).Specifically, "increased volatile organic compounds" and "increased ammonia" in the expression refer to a slight upward trend in the concentration of volatile organic compounds or ammonia in the air collected by the odor sensor relative to the baseline value. This is usually caused by pet excrement or body odor. "Increased local temperature" refers to a stable temperature difference between the local area monitored by the local ambient temperature sensor and the background temperature data, indicating that a heat source (such as a pet) has been present for a long time. "Increased PM2.5" and "increased PM10" refer to a slight upward trend in the concentration data of PM2.5 and PM10 collected by the particulate matter sensor relative to the baseline value. This may be caused by pet dander or hair shedding.

[0026] Specifically, the aforementioned adaptive purification strategy adjustments include: Fan speed fine-tuning; filter function optimization; directional airflow guidance.

[0027] Among these, fan speed fine-tuning refers to the precise adjustment of the fan speed inside the air purifier. Filter function optimization can be understood as the intelligent adjustment or enhancement of the filter function inside the air purifier based on actual purification needs. For example, the adsorption efficiency of certain filters (such as activated carbon filters) can be specifically activated or improved to more effectively remove odors or specific pollutants from pets. In practical applications, directional airflow guidance specifically involves controlling the direction of the air purifier's air outlet to precisely guide the purified airflow towards the direction of the inferred pet's location within the monitoring blind zone. The purpose is to create local circulation, accelerate air purification within the blind zone, and improve the comfort of the local environment.

[0028] In some preferred embodiments, the adaptive purification strategy adjustment is implemented as follows: Fine-tuning the fan speed can involve increasing the fan speed to 800-1200 RPM while ensuring the noise level remains below 30 dB to avoid unnecessary disturbance to stationary pets. Filter function optimization can include activating or enhancing the adsorption function of an adjustable activated carbon filter, for example, by using an electric field or heating to increase its adsorption capacity, or by increasing the fan speed to increase airflow through the filter, thereby improving purification efficiency without significantly increasing noise. Directional airflow guidance can be achieved by controlling the guide louvers or rotating the air outlet using a stepper motor or servo motor to fine-tune the airflow direction towards the inferred blind spot of the pet. For example, if the pet is inferred to be under the sofa, the airflow is directed to the area under the sofa to achieve rapid local air circulation and purification. In some preferred embodiments of the invention, the odor sensor employs a high-sensitivity semiconductor gas sensor, such as a metal oxide semiconductor (MOS) sensor; the local ambient temperature sensor employs at least two high-precision digital temperature sensors to monitor a stable temperature difference of 0.5-2 degrees Celsius between the local temperature and the background temperature; and the particulate matter sensor employs a laser scattering sensor. In some preferred embodiments of the present invention, the fan speed fine-tuning is set to increase the fan speed to 800-1200 RPM while ensuring that the noise level remains below 30 dB; the filter function optimization includes activating or enhancing the adsorption function of the activated carbon filter with adjustable adsorption efficiency, or increasing the airflow through the filter by increasing the fan speed; the directional airflow guidance is achieved by controlling the guide louvers or rotating the air outlet through a stepper motor or servo motor, thereby fine-tuning the airflow direction to the inferred direction of the pet's blind spot. Through the above technical solutions, this application can achieve more refined and efficient adaptive purification strategy adjustment after confirming the pet's intention to remain stationary in the monitoring blind spot for a long time. Specifically, while ensuring the pet's comfort (low noise), the air purification efficiency of the local area is improved, effectively solving the problem of local air pollution that may be caused by the pet in the blind spot. At the same time, through directional airflow guidance, the purification effect is accurately applied to the target area, avoiding energy waste and significantly improving the user experience and pet health care level. For example, the implementation process of the intelligent control method of the air purifier based on pet care in the embodiments of the present invention is illustrated below with a specific example. Suppose a pet (such as a cat) remains still under the sofa for an extended period, and the visual sensor and passive infrared sensor fail to detect clear pet activity signals within a preset time. At this point, the system will initiate multi-dimensional environmental anomaly signal acquisition and infer the pet's intention to remain stationary in the monitoring blind spot for an extended period. Once this intention is confirmed, the air purifier will activate an adaptive purification strategy adjustment. Specifically, the fan speed will be fine-tuned to approximately 1000 RPM, while the system will monitor and ensure the noise level remains around 28 dB to avoid disturbing the resting cat.Meanwhile, the activated carbon filter's adsorption function is enhanced to more effectively absorb odors (such as ammonia) that cats may produce. In addition, the system uses a stepper motor to precisely control the airflow louvers at the air outlet, finely adjusting the purified airflow to the area under the sofa, directly targeting the cat's blind spot, thus efficiently improving the air quality around the cat without disturbing it.

[0029] Corresponding to the intelligent control method for air purifiers based on pet care described in the above embodiments, Figure 2This diagram illustrates a structural block diagram of an intelligent air purifier control system based on pet care, according to an embodiment of this application. For ease of explanation, only the parts relevant to this embodiment are shown. The system includes: a main sensing unit, comprising a visual sensor and a passive infrared sensor, for collecting direct signals of pet activity; a main control unit, for continuously receiving data streams from the visual sensor and the passive infrared sensor, and when the visual sensor fails to recognize pet image features or the passive infrared sensor only detects intermittent signals below a first voltage threshold within a preset time, sending an instruction to activate the blind zone presence intent inference module; simultaneously sending an instruction to activate the multi-dimensional environmental anomaly signal acquisition unit; the multi-dimensional environmental anomaly signal acquisition unit includes an odor sensor, a local ambient temperature sensor, and a particulate matter sensor, for collecting multi-dimensional environmental anomaly signals; the odor sensor, local ambient temperature sensor, and particulate matter sensor... A temperature sensor and a particulate matter sensor collect data on the concentration of volatile organic compounds or ammonia in the air, local area and background temperature data, and PM2.5 and PM10 concentration data, respectively. A blind zone presence intent inference module, integrated into the main control unit or a separate coprocessor, is used to perform correlation analysis on the received multi-dimensional environmental anomaly signals and infer whether the pet has been stationary in the monitoring blind zone for an extended period. An adaptive purification strategy adjustment unit adjusts the air purifier's operating parameters when the blind zone presence intent inference unit confirms that the pet intends to remain stationary in the monitoring blind zone for an extended period. These adjustments include fan speed, filter optimization, and directional airflow guidance. This application's system integrates a main sensing unit, a main control unit, a multi-dimensional environmental anomaly signal acquisition unit, a blind zone presence intent inference module, and an adaptive purification strategy adjustment unit, forming a collaborative intelligent control architecture. This system overcomes the problem of insufficient identification and purification capabilities of traditional air purifiers when pets are in the monitoring blind zone. Specifically, the primary sensing unit is responsible for initial pet activity detection. When the detection results are uncertain, the main control unit coordinates the activation of the multi-dimensional environmental anomaly signal acquisition unit to collect supplementary data. Subsequently, the blind zone presence intent inference module performs in-depth analysis of this multi-dimensional data to accurately determine the pet's intention to remain stationary for an extended period in the blind zone. Finally, the adaptive purification strategy adjustment unit adjusts the air purifier's parameters precisely based on the judgment results, ensuring that the pet can enjoy continuous and effective air purification services in any area, significantly improving the intelligence and precision of indoor air quality management. In this embodiment, the primary sensing unit, as the system's primary sensing layer, can be designed in various ways. For example, the visual sensor can be a separate camera module connected to the main control unit via wired or wireless means; or it can be integrated into a specific location on the air purifier's casing, communicating with the main control unit via an internal bus. The passive infrared sensor can also be a separate PIR module, or integrated with the visual sensor in the same physical package.In some implementations, the main sensing unit can be designed to be detachable or angle-adjustable, allowing users to flexibly deploy it according to home layout and pet activity habits. In this embodiment, the main control unit is the core processing brain of the entire system, and its implementation can include various methods. For example, the main control unit can be an embedded system based on a microcontroller (MCU) or microprocessor (MPU), responsible for executing preset control logic and algorithms. In another implementation, the main control unit can be a more powerful single-board computer (such as a Raspberry Pi), possessing stronger computing power and scalability, capable of handling more complex image recognition and data analysis tasks. The main control unit can also communicate with a cloud server via a network interface (such as Wi-Fi or Bluetooth) to achieve remote control and data uploading. In this embodiment, the multi-dimensional environmental anomaly signal acquisition unit serves as an auxiliary sensing layer, and its implementation can be flexibly configured. For example, these sensors can be installed as independent modules in different locations on the air purifier, connecting to the main control unit through their respective interfaces. Alternatively, they can be integrated into a multi-sensor array to form a compact sensing module, communicating with the main control unit through a unified interface. In some implementations, these sensors may use analog outputs, requiring analog-to-digital converters (ADCs) to convert the signals into digital signals for processing by the main control unit.

[0030] In this embodiment, the blind zone presence inference module can be implemented in various ways. For example, it can be a software module running on the processor of the main control unit, analyzing sensor data by executing a preset algorithm (such as a rule-based expert system or a simple machine learning model). In another implementation, the module can be a separate hardware coprocessor dedicated to accelerating data analysis and pattern recognition, thereby reducing the computational burden on the main control unit. This module can also use a pre-trained model to extract and classify features from multi-dimensional environmental anomaly signals to determine the likelihood of a pet remaining stationary in the blind zone for an extended period. In this embodiment, the adaptive purification strategy adjustment unit is the execution layer for the system to perform purification tasks, and its implementation can include various methods. For example, it can be a hardware circuit composed of relays, motor drivers, and a PWM controller, used to control fan speed, filter function, and the movement of the air vents. In another implementation, this unit can be a software control module that sends control commands to the actuators of the air purifier (such as fan motors, filter drivers, stepper motors, or servo motors) to achieve fine-tuning of parameters. This unit can also dynamically adjust the purification strategy based on the inferred pet location and pollutant type, for example, prioritizing odor removal or enhancing particulate filtration. Furthermore, the system also includes a monitoring and mode switching module, used to switch back to the normal pet activity mode when the visual or passive infrared sensor re-detects a clear pet activity signal; and to switch back to the low-power mode when the multi-dimensional environmental anomaly signal continuously weakens and falls below a preset threshold within a preset time. Specifically, the monitoring and mode switching module is configured to continuously monitor data from the main sensing unit (including the visual sensor and passive infrared sensor) and the multi-dimensional environmental anomaly signal acquisition unit. When the visual sensor or passive infrared sensor re-captures a clear image of the pet's activity or a continuous signal above a first voltage threshold, it indicates that the pet has left the blind zone or resumed normal activity. At this time, the system will switch from the blind zone purification strategy back to the normal pet activity mode. The normal pet activity mode can be understood as a mode that purifies the air according to preset pet activity patterns or user-defined parameters. Specifically, when the abnormal signals such as odor, local ambient temperature, and particulate matter collected by the multi-dimensional environmental abnormal signal acquisition unit continuously weaken and fall below the preset judgment threshold within a preset time period, it indicates that the pet may have completely left the monitoring area, and the abnormal situation in the blind spot has been alleviated. In this case, the monitoring and mode switching module switches the system to a low-power mode. The low-power mode aims to minimize energy consumption, for example, by maintaining only basic air circulation or periodically performing low-intensity purification. Its purpose is to reduce energy consumption when there are no pets present or the environmental conditions are good. The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent control of parameters of a pet care air purifier, characterized in that, The method includes the following steps: It continuously receives data streams from the visual sensor and the passive infrared sensor. When no pet image features are identified within a preset time or only intermittent signals below the first voltage threshold are detected, it sends an activation blind zone presence inference command. Initiate multi-dimensional environmental anomaly signal acquisition, including data acquisition from odor sensors, local ambient temperature sensors, and particulate matter sensors; Correlation analysis was performed on the collected multidimensional environmental anomaly signals to infer the intention of the pet to remain stationary for a long time in the monitoring blind zone; When it is confirmed that the pet intends to remain stationary for an extended period within the monitoring blind spot, an adaptive purification strategy is adjusted.

2. The intelligent control method for pet care air purifier parameters according to claim 1, characterized in that, The method also includes continuous monitoring and mode switching steps: When the visual or passive infrared sensor detects a clear pet activity signal again, switch back to the regular pet activity mode; When the multidimensional environmental anomaly signal continues to weaken and falls below the judgment threshold within a preset time, switch back to low power mode.

3. The intelligent control method for pet care air purifier parameters according to claim 1, characterized in that, The odor sensor, local ambient temperature sensor, and particulate matter sensor respectively collect data on the concentration of volatile organic compounds or ammonia in the air, local area and background temperature data, and PM2.5 and PM10 concentration data, and monitor the slight upward trend of each indicator relative to the benchmark value.

4. The intelligent control method for pet care air purifier parameters according to claim 1, characterized in that, The association analysis includes: Time consistency assessment: Check whether each abnormal signal remains stable or continues to rise within a preset time period; Spatial correlation assessment: Analyze whether data from multiple sensors are concentrated in a specific direction or adjacent areas; Comprehensive threshold judgment: At least two abnormal signals simultaneously meet the time consistency requirement, and their intensity is lower than the conventional pollution trigger threshold.

5. The intelligent control method for pet care air purifier parameters according to claim 1, characterized in that, The logical expression for confirming that the pet remains still for an extended period within the monitoring blind zone is: Intent confirmation = ((Volatile organic compound increase AND ammonia increase) OR (Local temperature increase) OR (PM2.5 increase AND PM10 increase)) AND (At least two signals meet time consistency) AND (All signals meeting the conditions have strengths below the conventional trigger threshold).

6. The intelligent control method for pet care air purifier parameters according to claim 1, characterized in that, The adaptive purification strategy adjustment includes fine-tuning of fan speed, optimization of filter function, and directional airflow guidance.

7. The intelligent control method for pet care air purifier parameters according to claim 1, characterized in that, The odor sensor is a highly sensitive semiconductor gas sensor; The local ambient temperature sensor employs at least two high-precision digital temperature sensors to monitor a stable temperature difference of 0.5-2 degrees Celsius between the local temperature and the background temperature. The particulate matter sensor is a laser scattering sensor.

8. The intelligent control method for pet care air purifier parameters according to claim 6, characterized in that, The fan speed is fine-tuned to increase the fan speed to 800-1200 RPM, while keeping the noise level below 30dB; The filter function optimization includes activating or enhancing the adsorption function of an activated carbon filter with adjustable adsorption efficiency, or increasing the airflow through the filter by increasing the fan speed. The directional airflow guidance is achieved by controlling the airflow louvers or rotating air outlets via a stepper motor or servo motor, and fine-tuning the airflow direction to the direction of the inferred blind spot where the pet is located.

9. A smart control system for an air purifier based on pet care, characterized in that, The system includes: The main sensing units include a visual sensor and a passive infrared sensor, used to collect direct signals of pet activity; The main control unit is used to continuously receive data streams from the visual sensor and the passive infrared sensor. When the visual sensor fails to recognize pet image features or the passive infrared sensor only detects intermittent signals below the first voltage threshold within a preset time, it sends an instruction to activate the blind zone intention inference module; at the same time, it sends an instruction to start the multi-dimensional environmental abnormal signal acquisition unit. The multidimensional environmental anomaly signal acquisition unit includes an odor sensor, a local ambient temperature sensor, and a particulate matter sensor, which are used to acquire multidimensional environmental anomaly signals. The odor sensor, local ambient temperature sensor, and particulate matter sensor respectively acquire data on the concentration of volatile organic compounds or ammonia in the air, local area and background temperature data, and PM2.5 and PM10 concentration data. The blind zone presence intent inference module, integrated into the main control unit or independent coprocessor, is used to perform correlation analysis on the received multi-dimensional environmental anomaly signals and infer whether the pet has been stationary in the monitoring blind zone for a long time. An adaptive purification strategy adjustment unit is used to adjust the air purifier's operating parameters when the intent inference unit infers that the pet intends to remain stationary in the monitoring blind zone for an extended period of time. The adjustment of the air purifier's operating parameters includes adjusting the fan speed, optimizing the filter function, and guiding directional airflow.

10. The intelligent control system for an air purifier based on pet care according to claim 9, characterized in that, The system also includes: The monitoring and mode switching module is used to switch back to the normal pet activity mode when the visual or passive infrared sensor detects a clear pet activity signal again; and to switch back to the low power mode when the multidimensional environmental abnormal signal continues to weaken and falls below the judgment threshold within a preset time.

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