A smart home-based IoT control system for stoves

Abstract

This invention discloses a smart home-based IoT control system for stoves, specifically relating to the smart home field. It includes a stove IoT data acquisition module, a data transmission module, a data processing module, a stove status analysis module, a judgment module, and a feedback module. The stove IoT data acquisition module contains temperature, gas flow, smoke concentration, and flame status acquisition units, comprehensively collecting relevant data. The data transmission module communicates via local short-range and long-range wide-area network and encrypts the data. The data processing module cleans and transforms the collected data. The stove status analysis module constructs a cooking status and flame stability analysis model, obtaining corresponding indices and indicators. The judgment module judges the cooking and safety status based on this data. The feedback module displays information through a display screen and indicator lights. This system, through multi-dimensional data acquisition and precise analysis, upgrades the stove from traditional operation to intelligent control, comprehensively enhancing the safety of stove use.

Description

Technical Field

[0001] This invention relates to the field of smart home technology, and more specifically, to a smart home-based Internet of Things (IoT) control system for stoves. Background Technology

[0002] With the deep integration of IoT technology and the smart home industry, the intelligent upgrading of home kitchen equipment has become a trend. As a core piece of kitchen equipment, the safety, convenience, and energy efficiency of stoves have become the focus of users' attention. Traditional stoves mostly rely on manual operation to control the heat and cooking time, lacking the ability to monitor and dynamically adjust the cooking process in real time, making it difficult to meet the needs of modern families for an intelligent cooking experience.

[0003] Against this backdrop, building a stove IoT control system that integrates comprehensive data collection, secure encrypted transmission, intelligent analysis and judgment, and real-time feedback has become a key requirement for improving the intelligence level of stoves, ensuring safe use, and optimizing the cooking experience.

[0004] However, in actual use, it still has some shortcomings. For example, the existing technology does not collect key data such as stove temperature, gas flow, smoke concentration, and flame status in a comprehensive and accurate manner, nor can it effectively process and provide real-time feedback to users. Users cannot keep track of the stove's working status and cooking progress in a timely manner. In terms of safety monitoring, the existing technology mostly uses simple threshold judgments and is insufficient in monitoring complex safety conditions such as flame stability. Alarms are often issued only when safety hazards are already obvious, resulting in a delayed response. Moreover, the safety monitoring dimensions are singular, making it difficult to comprehensively ensure the safety of stove use. Most existing stoves cannot be connected to the Internet of Things, cannot achieve information sharing and linkage control with other smart home devices, and cannot be integrated into the overall smart home system, which limits the expansion of their intelligent functions. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a smart home-based stove Internet of Things control system, which solves the problems mentioned in the background art through the following solutions.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a smart home-based stove IoT control system, comprising a stove IoT data acquisition module, a data transmission module, a data processing module, a stove status analysis module, a judgment module, and a feedback module;

[0007] The stove IoT data acquisition module includes a temperature acquisition unit, a gas flow acquisition unit, a smoke concentration acquisition unit, and a flame status acquisition unit, which are used to collect stove IoT data and transmit the data to the data processing module.

[0008] The temperature acquisition unit includes a heating element temperature acquisition subunit, a cookware temperature acquisition subunit, and an ambient temperature acquisition subunit.

[0009] The data transmission module includes a local short-range communication unit and a long-range wide area network communication unit, used to encrypt the transmitted data;

[0010] The data processing module is used to perform data cleaning and data conversion operations on the data collected by the stove IoT data acquisition module, and transmit the processed data to the stove status analysis module.

[0011] The stove status analysis module is used to construct a cooking status analysis model and a flame stability analysis model based on the processed data, obtain the cooking status index and the flame stability index, and transmit the cooking status index and the flame stability index to the judgment module.

[0012] The judgment module includes a cooking state judgment unit and a safety state judgment unit, which are used to judge the cooking state and safety state of the stove based on the cooking state index and the flame stability index.

[0013] The feedback module is used to display the current temperature, gas flow rate, and cooking status information in real time through an OLED display screen, and to indicate the system operating status through indicator lights.

[0014] Preferably, the temperature acquisition method of the heating element acquisition subunit is as follows: a K-type thermocouple temperature sensor is deployed at the center position of the surface of each heating element in the stove;

[0015] The temperature acquisition method of the cookware temperature acquisition subunit is as follows: An MLX90614 infrared temperature sensor is embedded in the center of the cookware placement area on the stove panel. The measurement range is -40℃ to 300℃, the measurement accuracy is ±0.5℃, and the sampling frequency is 10Hz.

[0016] The ambient temperature acquisition subunit acquires data as follows: An SHT30 digital temperature sensor is installed around the stove at a horizontal distance of 50cm and a height of 150cm from the edge of the stove surface. The measurement range is -40℃ to 125℃, the measurement accuracy is ±0.3℃, and the sampling frequency is 1Hz.

[0017] The gas flow acquisition unit is acquired as follows: A G1.6 turbine-type gas flow sensor is installed in series 10cm upstream of the gas inlet valve of the stove on the gas pipeline. The measurement range is 0.016m³ / h-2.5m³ / h, the measurement accuracy is 1.5 grade, and the sampling frequency is 1Hz. At the same time, an MPX5700 pressure sensor is installed in parallel at the same location. The measurement range is 0-700kPa, the measurement accuracy is ±1.5%FS, and the sampling frequency is 1Hz.

[0018] The smoke concentration acquisition unit acquires smoke using the following method: An MQ-2 semiconductor smoke sensor is installed at the center of the range hood inlet above the stove. The sensor has a measurement range of 100ppm-10000ppm, a measurement accuracy of ±10%FS, and a sampling frequency of 2Hz.

[0019] The acquisition method of the flame state acquisition unit is as follows: An R2868 ultraviolet flame sensor is installed 10cm vertically above the stove burner. The spectral response range is 185nm-260nm, the detection distance is 0-100cm, the response time is ≤10ms, and the sampling frequency is 5Hz.

[0020] Preferably, the local short-range communication unit adopts the ZigBee protocol, selects the CC2530 wireless communication module, operates in the 2.4GHz ISM band, has a communication rate of 250kbps, a transmission distance of 30m indoors, and establishes a star topology between the sensor node and the gateway through a ZigBee network. Each sensor node is assigned a unique 64-bit IEEE address.

[0021] The remote wide area network communication unit adopts NB-IoT technology. The gateway accesses the operator's network through the BC95-B5NB-IoT module, supports the frequency band of 850MHz, has a maximum downlink rate of 25.6kbps, and a maximum uplink rate of 66.7kbps.

[0022] Preferably, the data cleaning operation is as follows: Threshold ranges are set for temperature data: the heating element temperature threshold range is room temperature - 800℃, the cookware temperature threshold range is room temperature - 300℃, and the ambient temperature threshold range is -10℃ to 40℃. Data exceeding these ranges are considered outliers and corrected using a sliding average filter with a sliding window size of 5. For gas flow data, a threshold range of 0-2.5 m³ / h is set based on the pipeline's rated flow rate. Flow rate mutations exceeding these ranges are considered outliers and removed. For smoke concentration data, outliers greater than 10000 ppm or less than 100 ppm are removed. An amplitude-limiting filter is used; when the difference between two adjacent sample values ​​exceeds 2000 ppm, the previous valid value is taken.

[0023] The data conversion operation is as follows: The 0-5V analog voltage signal output by the thermocouple temperature sensor is converted into a digital signal using a 16-bit A / D converter. The conversion accuracy is ±1LSB, and the conversion rate can be configured from 8SPS to 860SPS. In practical applications, it is set to 128SPS. All collected data are normalized. Temperature data is mapped to the [0,1] interval, gas flow data is mapped to the [0,1] interval, and smoke concentration data is mapped to the [0,1] interval (0 corresponds to 100ppm, 1 corresponds to 10000ppm). The normalization formula is: Where X is the original data, X min To measure the lower limit, X max This represents the upper limit of measurement.

[0024] Preferably, the cooking state analysis model is as follows:

[0025] C = α1T + α2F + α3S + β, where C represents the cooking state index, ranging from 0 to 1, where 0 indicates cooking has not started and 1 indicates cooking is complete; T represents the normalized cookware temperature; F represents the normalized gas flow rate; S represents the normalized smoke concentration; α1, α2, and α3 are regression coefficients; and β is a constant term. The values ​​are obtained by training on 500 sets of standard cooking data and fitting using the least squares method.

[0026] Preferably, the flame stability analysis model is as follows:

[0027] Where I refers to the flame stability index, This refers to the average historical normal flame flashing frequency calculated based on 300 sets of flame flashing frequency data under normal combustion conditions. This refers to the calculation of the standard deviation of historical normal flame flashing frequency based on 300 sets of flame flashing frequency data under normal combustion conditions, where f is the current flame flashing frequency.

[0028] Preferably, the method for determining the cooking state is as follows:

[0029] When the calculated cooking status index C ≥ 0.9, the system determines that cooking is about to be completed and sends a notification command to the user terminal through the smart home gateway. The cooking status index is divided into stages: C < 0.3 is the heating stage, and the system controls the gas flow rate to maintain at 0.8-2.5 m³ / h; 0.3 ≤ C < 0.9 is the heat preservation stage, and the gas flow rate is controlled at 0.2-0.8 m³ / h; C ≥ 0.9 is the completion stage, and the gas flow rate gradually decreases to 0. The flow rate adjustment is achieved by controlling the gas proportional valve. The proportional valve input signal is 0-5V, corresponding to a flow rate of 0-2.5 m³ / h, and the control accuracy is ±0.05 m³ / h.

[0030] Preferably, the method for determining the safety status is as follows: when the flame stability index When the duration is ≥3s, or the smoke concentration is ≥5000ppm for ≥2s, the system triggers a safety control command, closes the gas solenoid valve through the relay module, the relay action time is ≤10ms, the solenoid valve response time is ≤50ms, the audible and visual alarm device is activated, and alarm information is sent to the user terminal through the NB-IoT module. The alarm information includes the abnormality type, occurrence time, and current parameter value.

[0031] The technical effects and advantages of this invention are as follows:

[0032] The stove IoT data acquisition module of the present invention includes multiple acquisition units, which can comprehensively collect data such as heating element temperature, cookware temperature, ambient temperature, gas flow, smoke concentration, and flame status. Each acquisition unit adopts a high-precision sensor to ensure the accuracy of the data. At the same time, the feedback module displays relevant information in real time through an OLED display screen and indicator lights, allowing users to keep track of the stove status.

[0033] This invention establishes a flame stability analysis model, which, combined with smoke concentration monitoring, enables dynamic and multi-dimensional monitoring of the stove's safety status. When the flame stability index remains abnormal for a certain period of time or the smoke concentration exceeds the standard for a certain period of time, it can quickly trigger a safety control command, resulting in a fast response speed and greatly improving safety.

[0034] The data transmission module of this invention includes a local short-range communication unit and a remote wide area network communication unit, supports encrypted data transmission, enables the stove to connect to the Internet of Things, and can be linked with smart home devices such as user terminals to achieve remote control and information interaction, thus better integrating into the smart home system. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of the overall structure of the present invention. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] As attached Figure 1 The stove IoT control system shown includes a stove IoT data acquisition module, a data transmission module, a data processing module, a stove status analysis module, a judgment module, and a feedback module.

[0038] The stove IoT data acquisition module includes a temperature acquisition unit, a gas flow acquisition unit, a smoke concentration acquisition unit, and a flame status acquisition unit, which are used to collect stove IoT data and transmit the data to the data processing module.

[0039] The temperature acquisition unit includes a heating element temperature acquisition subunit, a cookware temperature acquisition subunit, and an ambient temperature acquisition subunit.

[0040] The temperature acquisition method of the heating element temperature acquisition subunit is as follows: A K-type thermocouple temperature sensor is deployed at the center of the surface of each heating element in the stove. Its measurement range is 0℃-800℃ and the measurement accuracy is ±0.5℃. The K-type thermocouple has good linearity and high stability in this temperature range. It is a commonly used sensor for temperature measurement in industrial and civil equipment. In practical applications, it can stably acquire the temperature of the heating element.

[0041] The acquisition method of the cookware temperature acquisition subunit is as follows: An MLX90614 infrared temperature sensor is embedded in the center of the cookware placement area on the stove panel. The measurement range is -40℃ to 300℃, the measurement accuracy is ±0.5℃, and the sampling frequency is 10Hz. This model of sensor is a mature commercial product and has been widely used in non-contact temperature measurement scenarios. It can accurately acquire the bottom temperature of the cookware.

[0042] The ambient temperature acquisition subunit acquires temperature using the following method: An SHT30 digital temperature sensor is installed around the stove at a horizontal distance of 50cm and a height of 150cm from the edge of the stove surface. The sensor has a measurement range of -40℃ to 125℃, a measurement accuracy of ±0.3℃, and a sampling frequency of 1Hz. The SHT30 sensor has an I2C interface and outputs digital signals. It is widely used in smart home environmental monitoring and can stably acquire ambient temperature.

[0043] The gas flow acquisition unit uses the following method: A G1.6 turbine-type gas flow sensor is installed in series 10cm upstream of the gas inlet valve of the stove on the gas pipeline. The measurement range is 0.016m³ / h-2.5m³ / h, the measurement accuracy is 1.5 class, and the sampling frequency is 1Hz. This type of sensor is a standard product in the field of gas metering, conforms to relevant national metrological standards, and can accurately acquire gas flow. At the same time, an MPX5700 pressure sensor is installed in parallel at the same location. The measurement range is 0-700kPa, the measurement accuracy is ±1.5%FS, and the sampling frequency is 1Hz. The MPX5700 is a commercial pressure sensor that can reliably acquire the pressure inside the gas pipeline.

[0044] The smoke concentration acquisition unit collects smoke using the following method: An MQ-2 semiconductor smoke sensor is installed at the center of the range hood inlet above the stove. The measurement range is 100ppm-10000ppm, the measurement accuracy is ±10%FS, and the sampling frequency is 2Hz. The MQ-2 sensor has good sensitivity to smoke, liquefied gas, etc., and has been practically applied in kitchen smoke monitoring, effectively collecting smoke concentration.

[0045] The acquisition method of the flame status acquisition unit is as follows: An R2868 ultraviolet flame sensor is installed 10cm vertically above the stove burner. The spectral response range is 185nm-260nm, the detection distance is 0-100cm, the response time is ≤10ms, and the sampling frequency is 5Hz. The R2868 sensor is specifically used for flame detection and can accurately detect the presence of flame and the flame flicker frequency. It is a mature technology in flame monitoring of gas equipment.

[0046] The data transmission module includes a local short-range communication unit and a long-range wide area network communication unit, used to encrypt the transmitted data;

[0047] It should be noted that the local short-range communication unit adopts the ZigBee protocol, selects the CC2530 wireless communication module, operates in the 2.4GHz ISM band, has a communication rate of 250kbps, and can transmit up to 30m indoors. The sensor node and the gateway form a star topology through the ZigBee network, and each sensor node is assigned a unique 64-bit IEEE address.

[0048] The remote wide area network communication unit adopts NB-IoT technology. The gateway accesses the operator's network through the BC95-B5 NB-IoT module, supports the B5 (850MHz) frequency band, has a maximum downlink rate of 25.6kbps, and a maximum uplink rate of 66.7kbps.

[0049] The data processing module is used to perform data cleaning and data conversion operations on the data collected by the stove IoT data acquisition module, and transmit the processed data to the stove status analysis module.

[0050] The data cleaning operation is as follows: Threshold ranges are set for temperature data: heating element temperature threshold range is room temperature - 800℃, cookware temperature threshold range is room temperature - 300℃, and ambient temperature threshold range is -10℃ to 40℃. Data exceeding these ranges are considered outliers and corrected using a sliding average filter with a sliding window size of 5. Gas flow data has a threshold range of 0-2.5 m³ / h based on the pipeline's rated flow rate. Abrupt flow values ​​exceeding this range (change rate exceeding 0.5 m³ / h / s) are considered outliers and removed. Smoke concentration data is filtered to remove outliers greater than 10000 ppm or less than 100 ppm. An amplitude-limiting filter is used; when the difference between two adjacent sampling values ​​exceeds 2000 ppm, the previous valid value is taken.

[0051] The data conversion operation is as follows: The 0-5V analog voltage signal output by the thermocouple temperature sensor is converted into a digital signal using a 16-bit A / D converter (model ADS1115). The conversion accuracy is ±1LSB, and the conversion rate can be configured from 8SPS to 860SPS. In practical applications, it is set to 128SPS. All collected data are normalized. Temperature data is mapped to the [0,1] interval (0 corresponds to the lower limit of measurement, 1 corresponds to the upper limit of measurement), gas flow data is mapped to the [0,1] interval (0 corresponds to 0 m³ / h, 1 corresponds to 2.5 m³ / h), and smoke concentration data is mapped to the [0,1] interval (0 corresponds to 100ppm, 1 corresponds to 10000ppm). The normalization formula is: Where X is the original data, X min To measure the lower limit, X max This represents the upper limit of measurement.

[0052] The stove status analysis module is used to construct a cooking status analysis model and a flame stability analysis model based on the processed data, obtain the cooking status index and the flame stability index, and transmit the cooking status index and the flame stability index to the judgment module.

[0053] The specific cooking state analysis model is as follows:

[0054] C = α1T + α2F + α3S + β, where C represents the cooking state index, ranging from 0 to 1, where 0 indicates cooking has not started and 1 indicates cooking is complete; T represents the normalized cookware temperature; F represents the normalized gas flow rate; S represents the normalized smoke concentration; α1, α2, and α3 are regression coefficients; and β is a constant term. The values ​​are obtained by training on 500 sets of standard cooking data and fitting using the least squares method.

[0055] The flame stability analysis model is as follows:

[0056] Where I refers to the flame stability index, This refers to the average historical normal flame flashing frequency calculated based on 300 sets of flame flashing frequency data under normal combustion conditions. This refers to the calculation of the standard deviation of historical normal flame flashing frequency based on 300 sets of flame flashing frequency data under normal combustion conditions, where f is the current flame flashing frequency.

[0057] The judgment module includes a cooking state judgment unit and a safety state judgment unit, which are used to judge the cooking state and safety state of the stove based on the cooking state index and the flame stability index.

[0058] The method for determining the cooking state is as follows:

[0059] When the calculated cooking status index C ≥ 0.9, the system determines that cooking is about to be completed and sends a notification command to the user terminal through the smart home gateway. The cooking status index is divided into stages: C < 0.3 is the heating stage, and the system controls the gas flow rate to maintain at 0.8-2.5 m³ / h; 0.3 ≤ C < 0.9 is the heat preservation stage, and the gas flow rate is controlled at 0.2-0.8 m³ / h; C ≥ 0.9 is the completion stage, and the gas flow rate gradually decreases to 0. The flow rate adjustment is achieved by controlling the gas proportional valve (model VGH-12). The proportional valve input signal is 0-5V, corresponding to a flow rate of 0-2.5 m³ / h, and the control accuracy is ±0.05 m³ / h.

[0060] The method for determining the safety status is as follows: when the flame stability index When the duration is ≥3s, or the smoke concentration is ≥5000ppm for ≥2s, the system triggers a safety control command, closes the gas solenoid valve (model ZCM-15) through the relay module (model G5V-1), the relay action time is ≤10ms, the solenoid valve response time is ≤50ms, and the audible and visual alarm device is activated (alarm sound pressure level ≥85dB, alarm light is a red LED flashing, frequency 2Hz), and sends alarm information to the user terminal through the NB-IoT module. The alarm information includes the abnormality type, occurrence time, and current parameter value.

[0061] The feedback module is used to display the current temperature, gas flow rate, and cooking status information in real time through an OLED display screen, and to indicate the system operating status through indicator lights;

[0062] It should be noted that a solid green light on the indicator indicates normal operation, a flashing yellow light indicates a warning, and a solid red light indicates a malfunction.

[0063] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other.

[0064] In conclusion, 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, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A smart home-based IoT control system for stoves, characterized in that, include: The stove IoT data acquisition module, data transmission module, data processing module, stove status analysis module, judgment module, and feedback module; The stove IoT data acquisition module includes a temperature acquisition unit, a gas flow acquisition unit, a smoke concentration acquisition unit, and a flame status acquisition unit, which are used to collect stove IoT data and transmit the data to the data processing module. The temperature acquisition unit includes a heating element temperature acquisition subunit, a cookware temperature acquisition subunit, and an ambient temperature acquisition subunit. The data transmission module includes a local short-range communication unit and a long-range wide area network communication unit, used to encrypt the transmitted data; The data processing module is used to perform data cleaning and data conversion operations on the data collected by the stove IoT data acquisition module, and transmit the processed data to the stove status analysis module. The stove status analysis module is used to construct a cooking status analysis model and a flame stability analysis model based on the processed data, obtain the cooking status index and the flame stability index, and transmit the cooking status index and the flame stability index to the judgment module. The specific cooking state analysis model is as follows: C = α1T + α2F + α3S + β, where C represents the cooking state index, ranging from 0 to 1, where 0 indicates cooking has not started and 1 indicates cooking is complete; T represents the normalized cookware temperature; F represents the normalized gas flow rate; S represents the normalized smoke concentration; α1, α2, and α3 are regression coefficients; and β is a constant term. The values ​​are obtained by training on 500 sets of standard cooking data and fitting using the least squares method. The judgment module includes a cooking state judgment unit and a safety state judgment unit, which are used to judge the cooking state and safety state of the stove based on the cooking state index and the flame stability index. The feedback module is used to display the current temperature, gas flow rate, and cooking status information in real time through an OLED display screen, and to indicate the system operating status through indicator lights.

2. The stove IoT control system based on smart home as described in claim 1, characterized in that: The temperature acquisition method of the heating element acquisition subunit is as follows: a K-type thermocouple temperature sensor is deployed at the center of the surface of each heating element in the stove; The temperature acquisition method of the cookware temperature acquisition subunit is as follows: An MLX90614 infrared temperature sensor is embedded in the center of the cookware placement area on the stove panel. The measurement range is -40℃ to 300℃, the measurement accuracy is ±0.5℃, and the sampling frequency is 10Hz. The ambient temperature acquisition subunit acquires data as follows: An SHT30 digital temperature sensor is installed around the stove at a horizontal distance of 50cm and a height of 150cm from the edge of the stove surface. The measurement range is -40℃ to 125℃, the measurement accuracy is ±0.3℃, and the sampling frequency is 1Hz. The gas flow acquisition unit is acquired as follows: A G1.6 turbine-type gas flow sensor is installed in series 10cm upstream of the gas inlet valve of the stove on the gas pipeline. The measurement range is 0.016m³ / h-2.5m³ / h, the measurement accuracy is 1.5 grade, and the sampling frequency is 1Hz. At the same time, an MPX5700 pressure sensor is installed in parallel at the same location. The measurement range is 0-700kPa, the measurement accuracy is ±1.5%FS, and the sampling frequency is 1Hz. The smoke concentration acquisition unit acquires smoke using the following method: An MQ-2 semiconductor smoke sensor is installed at the center of the range hood inlet above the stove. The sensor has a measurement range of 100ppm-10000ppm, a measurement accuracy of ±10%FS, and a sampling frequency of 2Hz. The acquisition method of the flame state acquisition unit is as follows: An R2868 ultraviolet flame sensor is installed 10cm vertically above the stove burner. The spectral response range is 185nm-260nm, the detection distance is 0-100cm, the response time is ≤10ms, and the sampling frequency is 5Hz.

3. The stove IoT control system based on smart home as described in claim 1, characterized in that: The local short-range communication unit adopts the ZigBee protocol, selects the CC2530 wireless communication module, operates in the 2.4GHz ISM band, has a communication rate of 250kbps, and a transmission distance of 30m indoors. The sensor nodes and the gateway form a star topology through the ZigBee network, and each sensor node is assigned a unique 64-bit IEEE address. The remote wide area network communication unit adopts NB-IoT technology. The gateway accesses the operator's network through the BC95-B5NB-IoT module, supports the frequency band of 850MHz, has a maximum downlink rate of 25.6kbps, and a maximum uplink rate of 66.7kbps.

4. A stove IoT control system based on smart home technology according to claim 1, characterized in that: The data cleaning operation is as follows: Threshold ranges are set for temperature data: heating element temperature threshold range is room temperature - 800℃, cookware temperature threshold range is room temperature - 300℃, and ambient temperature threshold range is -10℃ to 40℃. Data exceeding these ranges are considered outliers and corrected using a sliding average filter with a sliding window size of 5. For gas flow data, a threshold range of 0-2.5 m³ / h is set based on the pipeline's rated flow rate. Abrupt flow values ​​exceeding these ranges are considered outliers and removed. For smoke concentration data, outliers greater than 10000 ppm or less than 100 ppm are removed using an amplitude limiting filter. When the difference between two adjacent sample values ​​exceeds 2000 ppm, the previous valid value is taken. The data conversion operation is as follows: The 0-5V analog voltage signal output by the thermocouple temperature sensor is converted into a digital signal using a 16-bit A / D converter. The conversion accuracy is ±1LSB, and the conversion rate can be configured from 8SPS to 860SPS. In practical applications, it is set to 128SPS. All collected data are normalized, with temperature data mapped to the [0,1] interval, gas flow data mapped to the [0,1] interval, and smoke concentration data mapped to the [0,1] interval. The normalization formula is: Where X is the original data, X min To measure the lower limit, X max This represents the upper limit of measurement.

5. A stove IoT control system based on smart home technology according to claim 1, characterized in that: The flame stability analysis model is as follows: Where I refers to the flame stability index, This refers to the average historical normal flame flashing frequency calculated based on 300 sets of flame flashing frequency data under normal combustion conditions. This refers to the calculation of the standard deviation of historical normal flame flashing frequency based on 300 sets of flame flashing frequency data under normal combustion conditions, where f is the current flame flashing frequency.

6. A stove IoT control system based on smart home technology according to claim 1, characterized in that: The method for determining the cooking state is as follows: When the calculated cooking status index C ≥ 0.9, the system determines that cooking is about to be completed and sends a notification command to the user terminal through the smart home gateway. The cooking status index is divided into stages: C < 0.3 is the heating stage, and the system controls the gas flow rate to maintain at 0.8-2.5 m³ / h; 0.3 ≤ C < 0.9 is the heat preservation stage, and the gas flow rate is controlled at 0.2-0.8 m³ / h; C ≥ 0.9 is the completion stage, and the gas flow rate gradually decreases to 0. The flow rate adjustment is achieved by controlling the gas proportional valve. The proportional valve input signal is 0-5V, corresponding to a flow rate of 0-2.5 m³ / h, and the control accuracy is ±0.05 m³ / h.

7. A smart home-based stove IoT control system according to claim 5, characterized in that: The method for determining the safety status is as follows: when the flame stability index When the duration is ≥3s, or the smoke concentration is ≥5000ppm for ≥2s, the system triggers a safety control command, closes the gas solenoid valve through the relay module, the relay action time is ≤10ms, the solenoid valve response time is ≤50ms, the audible and visual alarm device is activated, and alarm information is sent to the user terminal through the NB-IoT module. The alarm information includes the abnormality type, occurrence time, and current parameter value.

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