Non-inductive health monitoring and stress early warning intelligent nest mat for pets and control method

Abstract

The invention discloses a pet non-inductive health monitoring and stress early warning intelligent nest mat and a control method, and belongs to the technical field of pet intelligent articles and intelligent control. Pet physiological parameters are synchronously collected through the piezoelectric pressure sensor and the infrared temperature sensor, the stress level is quantitatively judged based on an AI algorithm model, graded early warning and matching type relieving intervention are triggered according to the stress level, and meanwhile a low-power-consumption control mechanism is carried to achieve long endurance. The intelligent nest mat is of a three-layer detachable waterproof structure and supports a double-sensor high-precision scheme and a single-sensor low-cost scheme at the same time, and all the modules work cooperatively to achieve a whole-process closed loop of monitoring, early warning and relieving. The system solves the problems of wearing resistance, low monitoring precision, untimely early warning, inactive relieving and the like of pets, is suitable for family health monitoring of common pets such as dogs, cats and the like, and has the advantages of non-inductive monitoring, accurate identification, intelligent intervention, low power consumption, flexible scheme and the like.

Description

A smart pet bed and stress warning system with non-intrusive health monitoring and control method Technical Field

[0001] The purpose of this invention is to overcome the shortcomings of the prior art and provide a smart pet bed and control method for non-intrusive health monitoring and stress early warning, realizing integrated functions of non-wearable non-intrusive monitoring, quantitative stress identification, graded early warning, automatic soothing intervention and cloud data management. Background Technology

[0002] Currently, pet health monitoring primarily relies on wearable collars, which pets resist, experience discomfort, and are prone to additional stress reactions. Stress interventions are mostly passive, lacking seamless, real-time, and integrated monitoring and early warning solutions. Ordinary pet beds only provide rest and cannot achieve health management or emotional soothing. Existing technologies often use single sensors to collect data, resulting in limitations such as limited monitoring dimensions, lack of quantitative standards for stress identification, susceptibility to environmental interference, high power consumption, and short battery life. Furthermore, they fail to implement a closed-loop control method encompassing monitoring, identification, early warning, and relief, making it difficult to meet pet owners' needs for refined pet health monitoring. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a smart pet bed and control method for non-intrusive health monitoring and stress early warning. This integrated system achieves non-wearable, non-intrusive monitoring, quantitative stress identification, graded early warning, automatic soothing intervention, and cloud data management, addressing pain points such as pet resistance to wearing devices, low monitoring accuracy, untimely early warning, lack of active soothing, and short device battery life. The invention employs the following technical solutions: Method level: Physiological parameters are simultaneously collected using a piezoelectric pressure sensor and an infrared temperature sensor. A three-layer AI algorithm model is used to quantitatively determine the stress level. Based on the stress level, graded early warning and matched soothing intervention are triggered. A low-power control mechanism is also incorporated to achieve intelligent and non-intrusive monitoring of pet health. Device level: The smart bed includes the bed body and embedded non-intrusive physiological monitoring modules, stress identification modules, main control modules, wireless communication modules, soothing release modules, and power supply modules. These modules work collaboratively to provide hardware support for the control method. The beneficial effects of this invention are as follows: 1. Methodological innovation: This invention proposes a complete closed-loop control method for pet stress monitoring, early warning, and relief, achieving full automation from data collection to intervention termination, overcoming the shortcomings of passive intervention in existing technologies. 2. Seamless and non-wearable: Multi-parameter monitoring can be performed while the pet is lying down, without restraint or resistance, avoiding the additional stress caused by wearable devices. 3. Dual-sensor accurate monitoring: Pressure and infrared temperature sensors work together to collect data, combined with bandpass filtering, ambient temperature compensation, and adaptive acquisition thresholds, effectively eliminating environmental interference and achieving high monitoring accuracy. 4. Quantitative stress identification: Based on AI algorithm models and a basic parameter library of pet breeds, a clear stress quantification threshold is established to achieve accurate identification of mild / severe stress. 5. Tiered early warning + automatic relief: Early warning and relief are linked and matched, providing timely and intelligent intervention; relief automatically stops after the pet recovers. 6. Low power consumption and long battery life: Equipped with a low-power triggering mechanism and dual-mode communication design, the device's battery life is significantly improved, meeting the needs of long-term use. 7. Removable and easy to clean: The three-layer structure is removable and connected via Velcro, with a sealed waterproof compartment rated IP67, balancing practicality and hygiene. 8. Dual-mode communication + cloud storage: Bluetooth enables local short-range data transmission, while WiFi enables remote cloud data upload, supporting 24 / 7 health data storage and viewing. Figure 1 is a schematic diagram of the overall structure of the smart mattress of the present invention, wherein: 1 - breathable mesh skin-friendly fabric, 2 - memory foam cushioning filling layer, 3 - food-grade silicone sealed waterproof chamber, 4 - piezoelectric pressure sensor, 5 - infrared temperature sensor, 6 - main control module, 7 - soothing release module, 8 - lithium polymer power supply module, 9 - Bluetooth + WiFi dual-mode wireless communication module; all sensors are evenly distributed in the central area of ​​the mattress, with a spacing of 8-10cm, and flush with the inner wall of the waterproof chamber. Figure 2 is a flowchart of the control method of the present invention, showing the entire control logic from physiological parameter acquisition (S1), core feature extraction (S2), stress level determination (S3), graded early warning and soothing intervention (S4), stress relief and low power consumption control (S5). Figure 3 is a block diagram of the module connection of the present invention, showing the connection between the piezoelectric pressure sensor, the infrared temperature sensor and the stress recognition module, the connection between the stress recognition module and the main control module, and the connection relationship between the main control module and the power supply module, the wireless communication module, the relief release module and the mobile APP, as well as the data transmission and control signal triggering process. Detailed Implementation (I) Smart Pet Bed Hardware Structure The pet bed itself consists of three layers: the outer layer is a breathable mesh fabric that is skin-friendly, ensuring breathability and comfort for the pet; the middle layer is a memory foam cushioning layer that conforms to the pet's body curves; the inner layer is a food-grade silicone sealed waterproof chamber with an IP67 waterproof rating. An integrated sensor mounting slot is provided inside for easy snap-fit ​​fixing and disassembly / replacement of each module. The non-contact physiological monitoring module is located in the center of the pet bed within the waterproof chamber. It includes a piezoelectric pressure sensor and an infrared temperature sensor, spaced 8-10cm apart, with the sensor surface flush with the inner wall of the waterproof chamber. The piezoelectric pressure sensor uses a 0.2-5Hz bandpass filter to process the collected pressure signal, accurately extracting the characteristic frequency signals corresponding to the pet's breathing and heart rate. The infrared temperature sensor is a non-contact temperature probe with a temperature measurement accuracy of ±0.1℃, automatically removing ambient temperature compensation values ​​when collecting the pet's body temperature. Both sensors use a 10Hz synchronous acquisition mode and can adaptively adjust the acquisition threshold according to the pet's body shape. (II) Specific Steps of Control Method S1: Physiological Parameter Acquisition A piezoelectric pressure sensor acquires the pet's heart rate, respiration, and body movement data, while an infrared temperature sensor acquires the pet's body surface temperature data. Both operate in a 10Hz synchronous acquisition mode. The piezoelectric pressure sensor performs 0.2-5Hz bandpass filtering on the acquired signals to filter out environmental vibration interference. The infrared temperature sensor automatically removes environmental temperature compensation values ​​to ensure the accuracy of temperature data. At the same time, the acquisition threshold is adaptively adjusted according to the pet's size (small / medium / large). S2: Core Feature Extraction The acquired physiological parameters are input into the AI ​​algorithm model of the stress recognition module. This model includes a feature extraction layer, an anomaly detection layer, and a result output layer. The feature extraction layer extracts three core features from the heart rate, body movement, and body temperature data: heart rate fluctuation value, body temperature change rate, and body movement frequency. S3: Stress Level Judgment The abnormal judgment layer is based on the pet breed's basic parameter library, comparing real-time characteristics with preset thresholds: - When the heart rate fluctuates by ≥20% from the baseline value, the body surface temperature changes by ≥0.5℃ / 10min, and the body movement frequency is ≥5 times / min, it is judged as a mild stress state; - When the above parameters are ≥30%, ≥1℃ / 10min, and the body movement frequency is ≥10 times / min respectively, it is judged as a severe stress state; The result output layer transmits the stress judgment result to the main control module in real time. S4: Graded Early Warning and Soothing Intervention The main control module receives the stress judgment result and triggers the corresponding graded early warning and soothing intervention: - Mild stress: The control wireless communication module pushes a text warning to the mobile APP, and at the same time activates the low-frequency vibration soothing device, which operates at a frequency of 50-80Hz; - Severe stress: The control wireless communication module pushes a dual text + voice warning to the mobile APP, and at the same time activates the low-frequency vibration soothing device and the pheromone release device, with a pheromone release amount of 0.5ml / h.S5: Stress Relief and Low Power Consumption Control When the stress recognition module determines that the pet's physiological parameters have returned to the normal range, the main control module automatically stops the operation of the soothing release module and pushes a stress relief prompt to the mobile APP; Low power consumption control: When the piezoelectric pressure sensor detects a pressure value ≥5N, it wakes up all working modules; when the pressure value <5N lasts for 10 minutes, it controls all modules to enter sleep mode, retaining only the main control module and pressure sensor in low power standby mode. In sleep mode, WiFi communication is stopped, and only Bluetooth 5.0 low power standby is retained. (III) Single Sensor Implementation In another embodiment, the non-sensory physiological monitoring module can use a piezoelectric pressure sensor or an infrared temperature sensor alone to meet the needs of low-cost, basic monitoring. When using a piezoelectric pressure sensor alone, only heart rate, respiration, and body movement data are collected, and the stress recognition module performs a simplified stress judgment based on the above data; when using an infrared temperature sensor alone, only body surface temperature monitoring and abnormal warning are realized. The main control module automatically matches the simplified algorithm to reduce data processing power consumption, further improving battery life in working mode. The connection relationships of the remaining modules, low-power control, early warning and mitigation logic are consistent with the dual-sensor implementation.

Claims

1. A control method for a pet-friendly, non-intrusive health monitoring and stress early warning smart bedding, characterized in that, Includes the following steps: S1: The pet's physiological parameters are collected non-contactly through the non-intrusive physiological monitoring module embedded in the bedding. These physiological parameters include heart rate, body temperature, and frequency of body movements. S2: Input the collected physiological parameters into the AI ​​algorithm model of the stress recognition module to extract three core features: heart rate fluctuation value, body temperature change rate, and body movement frequency; S3: Based on the pet breed basic parameter library, compare the real-time features with preset thresholds to determine the pet's stress level; S4: The main control module triggers a graded warning based on the stress level and controls the soothing release module to start the matching soothing intervention mode; S5: When the stress recognition module determines that the pet's physiological parameters have returned to normal, the main control module automatically stops the soothing intervention and pushes a stress relief prompt to the terminal APP.

2. The control method according to claim 1, characterized in that, In step S1, the non-sensory physiological monitoring module includes a piezoelectric pressure sensor and an infrared temperature sensor, both of which operate in a 10Hz synchronous acquisition mode. The piezoelectric pressure sensor uses a 0.2-5Hz bandpass filter to process the signal, and the infrared temperature sensor automatically removes the ambient temperature compensation value, with a temperature measurement accuracy of ±0.1℃.

3. The control method according to claim 2, characterized in that, Step S1 also includes: adaptively adjusting the sampling threshold according to the pet's size, reducing the stress sampling threshold for small pets, and increasing the temperature sampling distance for large pets.

4. The control method according to claim 1, characterized in that, In step S3, the stress level determination criteria are as follows: - Mild stress: heart rate fluctuation ≥20%, body temperature change ≥0.5℃ / 10min, body movement frequency ≥5 times / min; - Severe stress: heart rate fluctuation ≥30%, body temperature change ≥1℃ / 10min, body movement frequency ≥10 times / min.

5. The control method according to claim 1, characterized in that, In step S4, the graded warning includes: pushing only a text warning to the terminal APP when there is mild stress; and pushing both text and voice warnings to the terminal APP when there is severe stress.

6. The control method according to claim 1, characterized in that, In step S4, the soothing intervention mode includes: - Mild stress: only the low-frequency vibration soothing device is activated, operating at a frequency of 50-80Hz; - Severe stress: the low-frequency vibration soothing device and the pheromone release device are activated simultaneously, with a pheromone release rate of 0.5ml / h.

7. The control method according to claim 1, characterized in that, It also includes a low-power control step: when the piezoelectric pressure sensor detects a pressure value ≥5N, it wakes up each working module; when the pressure value <5N lasts for 10 minutes, it controls each module to enter sleep mode, keeping only the main control module and the pressure sensor in low-power standby mode.

8. The control method according to claim 7, characterized in that, In sleep mode, WiFi communication is stopped, and only Bluetooth 5.0 low-power standby is retained. The battery life is ≥30 days in dual-sensor continuous data acquisition mode and ≥90 days in sleep mode.

9. A smart pet bed with non-intrusive health monitoring and stress early warning, characterized in that, The device includes a pad body and embedded components such as: a non-sensory physiological monitoring module, a stress recognition module, a main control module, a wireless communication module, a relaxation release module, and a power supply module. The main control module executes the control method as described in any one of claims 1-8.

10. The smart mattress according to claim 9, characterized in that, The mattress body has a three-layer detachable structure: an outer layer of breathable mesh skin-friendly fabric, a middle layer of memory foam cushioning filling, and an inner layer of food-grade silicone sealed waterproof chamber (IP67 waterproof rating). Each module is snapped into the slots inside the waterproof chamber, and the three-layer structure is detachably connected by Velcro.

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