Intelligent cooker remote control and data analysis method and device based on Internet of Things

Abstract

The invention relates to the technical field of intelligent cooking utensils, and discloses an intelligent cooking utensil remote control and data analysis method and device based on the Internet of Things, and the method comprises the steps: obtaining a first use parameter of an intelligent cooking utensil in a first time period when a remote control instruction triggered by a user is received; according to the first use parameter, judging whether the intelligent cooker has at least one use abnormal item or not; when it is judged that at least one abnormal use item exists in the intelligent kitchen range, generating an abnormity processing strategy of the intelligent kitchen range according to all the abnormal use items; according to the exception handling strategy, remote control parameters of the intelligent kitchen range are generated so as to regulate and control the intelligent kitchen range. Therefore, the intelligent control accuracy of the cooker can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart cookers, and in particular to a method and device for remote control and data analysis of smart cookers based on the Internet of Things. Background Art

[0002] With the rapid development of smart home technology, more and more traditional kitchen appliances are becoming intelligent, which improves the convenience of using kitchen appliances.

[0003] Taking stoves as an example, current control of stoves mainly relies on active control by users, mainly including immediate active control and scheduled active control. However, practice has found that among user groups, especially vulnerable groups, there are often negligence and improper control of stoves during the cooking process, such as forgetting to turn off / completely turn off the gas valve, heating the stove for too long, etc., which leads to kitchen safety accidents and causes great losses to the users' lives and property.

[0004] It can be seen that how to improve the accuracy of intelligent control of stoves is particularly important. Summary of the Invention

[0005] The present invention provides an Internet of Things-based intelligent cooker remote control and data analysis method and device, which can improve the intelligent control accuracy of the cooker.

[0006] In order to solve the above technical problems, the first aspect of the present invention discloses a remote control and data analysis method for an intelligent cooker based on the Internet of Things, the method comprising: When a remote control command triggered by a user is received, obtaining a first usage parameter of the smart cooker within a first time period; determining, based on the first usage parameter, whether the smart cooker has at least one abnormal usage item; When it is determined that the smart cooker has at least one abnormal usage item, generating an abnormality handling strategy for the smart cooker according to all the abnormal usage items; According to the exception handling strategy, remote control parameters of the smart cooker are generated to regulate the smart cooker.

[0007] As an optional embodiment, in the first aspect of the present invention, before obtaining the first usage parameter of the smart cooker within the first time period, the method further includes: Parsing the remote control instruction to obtain data analysis requirement parameters of the remote control instruction; matching a target direction parameter of the smart cooker according to the data analysis requirement parameter, where the target direction parameter is used to indicate a direction for obtaining the first usage parameter of the smart cooker; Furthermore, the smart cooker includes at least one target module, and the target module is used to complete a target function corresponding to the smart cooker. The step of obtaining a first usage parameter of the smart cooker within a first time period includes: According to the target direction parameter, matching the associated module associated with the target direction parameter among all the target modules; Determining a target sensing range of the smart cooker based on all the associated modules; A first usage parameter of the smart cooker within a first time period is acquired according to the target sensing range.

[0008] As an optional embodiment, in the first aspect of the present invention, the first usage parameter includes at least one type of first usage sub-parameter selected from the group consisting of a gas usage parameter, a heating usage parameter, a power usage parameter, a heat dissipation usage parameter, a radiation usage parameter, a usage time parameter, and a usage object parameter. Determining whether the smart cooker has at least one abnormal usage item based on the first usage parameter includes: determining, according to the data analysis requirement parameter, a second usage parameter of the smart cooker within a second time period, where the second usage parameter corresponds to the first usage parameter; For each type of second usage sub-parameter in the second usage parameter, calculating a usage trajectory reference parameter range of the second usage sub-parameter of the type according to the second usage sub-parameter of the type within the second time period; For each type of first usage sub-parameter in the first usage parameter, determining whether the first usage sub-parameter of the type is within the usage trajectory reference parameter range of the corresponding same type; When it is determined that the first usage sub-parameter of this type is not within the usage trajectory reference parameter range corresponding to the same type, the first usage sub-parameter of this type is determined as an abnormal usage item of the smart cooker.

[0009] As an optional embodiment, in the first aspect of the present invention, generating an exception handling strategy for the smart cooker based on all the abnormal usage items includes: For each abnormal usage item, analyzing a preliminary impact object of the abnormal usage item, wherein the preliminary impact object is used to indicate the status of an object that is associated with and affected by the abnormal usage item, and each preliminary impact object has a corresponding target impact value, which is used to indicate the degree of impact of the abnormal usage item on the corresponding preliminary impact object; Determine a target influence object among all prepared influence objects according to all the target influence values, wherein all the target influence values ​​of the target influence object are greater than or equal to a preset target influence threshold; Obtaining target abnormal items related to the target impact object from among all the abnormal usage items; An exception handling strategy for the smart cooker is generated based on all the target exception items and their corresponding target impact values.

[0010] As an optional implementation manner, in the first aspect of the present invention, the target impact value is calculated as follows: Calculating a target distance value between the first usage sub-parameter of the usage abnormality item and the usage trajectory reference parameter range corresponding to the same type; sensing multi-dimensional parameters of the prepared impact object corresponding to the abnormal usage item, wherein the multi-dimensional parameters include at least two of attribute parameters, state parameters, age parameters, and configuration parameters; Calculate the target impact value corresponding to the prepared impact object according to the multi-dimensional parameter and the target distance value.

[0011] As an optional embodiment, in the first aspect of the present invention, the target impact object includes a corresponding preset priority value, and generating the exception handling strategy of the smart cooker based on all the target abnormal items and their corresponding target impact values ​​includes: Based on all the target abnormal items, an abnormal item association map is constructed to analyze the logical dependency and physical impact path between each target abnormal item; Generate an exception handling timeliness parameter and an exception handling intensity parameter for each target exception item according to the exception item association map, the target impact value corresponding to each target exception item, and the preset priority value of the target impact object; An exception handling strategy for the smart cooker is generated according to all the exception handling timeliness parameters and all the exception handling intensity parameters.

[0012] As an optional embodiment, in the first aspect of the present invention, generating remote control parameters of the smart cooker according to the exception handling strategy to regulate the smart cooker includes: determining, according to the abnormality handling strategy, a current control mechanism of the intelligent cooker, a target control parameter of the current control mechanism, and an expected control effect parameter of the target control parameter; sensing an environmental state parameter of the target control parameter; Analyzing, according to the environmental state parameters, the simulated control effect parameters of the target control parameters under the environmental state parameters; Calculating a matching value between the expected control effect parameter and the simulated control effect parameter; updating the target control parameter according to the matching value; According to the updated target control parameter and the current control mechanism, remote control parameters of the smart cooker are generated to regulate the smart cooker.

[0013] The second aspect of the present invention discloses a remote control and data analysis device for an intelligent cooker based on the Internet of Things, the device comprising: an acquisition module, configured to acquire a first usage parameter of the smart cooker within a first time period upon receiving a remote control instruction triggered by a user; a judgment module, configured to judge whether the smart cooker has at least one abnormal usage item according to the first usage parameter; a generating module, configured to generate an abnormality handling strategy for the smart cooker based on all the abnormal usage items when the judging module determines that the smart cooker has at least one abnormal usage item; The generating module is further configured to generate remote control parameters of the smart cooker according to the exception handling strategy, so as to regulate the smart cooker.

[0014] As an optional embodiment, in the second aspect of the present invention, the device further includes: a parsing module, configured to parse the remote control instruction to obtain a data analysis requirement parameter of the remote control instruction before the acquiring module acquires the first usage parameter of the smart cooker within the first time period; a matching module, configured to match a target direction parameter of the smart cooker according to the data analysis requirement parameter, wherein the target direction parameter is used to indicate an acquisition direction of the first usage parameter of the smart cooker; Furthermore, the smart cooker includes at least one target module, which is used to complete a target function corresponding to the smart cooker. The specific manner in which the acquisition module acquires the first usage parameter of the smart cooker within the first time period includes: According to the target direction parameter, matching the associated module associated with the target direction parameter among all the target modules; Determining a target sensing range of the smart cooker based on all the associated modules; A first usage parameter of the smart cooker within a first time period is acquired according to the target sensing range.

[0015] As an optional embodiment, in the second aspect of the present invention, the first usage parameter includes at least one type of first usage sub-parameter selected from the group consisting of a gas usage parameter, a heating usage parameter, a power usage parameter, a heat dissipation usage parameter, a radiation usage parameter, a usage time parameter, and a usage object parameter. The specific manner in which the judgment module judges whether the smart cooker has at least one abnormal usage item based on the first usage parameter includes: determining, according to the data analysis requirement parameter, a second usage parameter of the smart cooker within a second time period, where the second usage parameter corresponds to the first usage parameter; For each type of second usage sub-parameter in the second usage parameter, calculating a usage trajectory reference parameter range of the second usage sub-parameter of the type according to the second usage sub-parameter of the type within the second time period; For each type of first usage sub-parameter in the first usage parameter, determining whether the first usage sub-parameter of the type is within the usage trajectory reference parameter range of the corresponding same type; When it is determined that the first usage sub-parameter of this type is not within the usage trajectory reference parameter range corresponding to the same type, the first usage sub-parameter of this type is determined as an abnormal usage item of the smart cooker.

[0016] As an optional embodiment, in the second aspect of the present invention, the specific manner in which the generation module generates the exception handling strategy of the smart cooker based on all the abnormal usage items includes: For each abnormal usage item, analyzing a preliminary impact object of the abnormal usage item, wherein the preliminary impact object is used to indicate the status of an object that is associated with and affected by the abnormal usage item, and each preliminary impact object has a corresponding target impact value, which is used to indicate the degree of impact of the abnormal usage item on the corresponding preliminary impact object; Determine a target influence object among all prepared influence objects according to all the target influence values, wherein all the target influence values ​​of the target influence object are greater than or equal to a preset target influence threshold; Obtaining target abnormal items related to the target impact object from among all the abnormal usage items; An exception handling strategy for the smart cooker is generated based on all the target exception items and their corresponding target impact values.

[0017] As an optional implementation, in the second aspect of the present invention, the target impact value is calculated as follows: Calculating a target distance value between the first usage sub-parameter of the usage abnormality item and the usage trajectory reference parameter range corresponding to the same type; sensing multi-dimensional parameters of the prepared impact object corresponding to the abnormal usage item, wherein the multi-dimensional parameters include at least two of attribute parameters, state parameters, age parameters, and configuration parameters; Calculate the target impact value corresponding to the prepared impact object according to the multi-dimensional parameter and the target distance value.

[0018] As an optional embodiment, in the second aspect of the present invention, the target impact object includes a corresponding preset priority value, and the specific manner in which the generation module generates the exception handling strategy for the smart cooker based on all the target abnormal items and their corresponding target impact values ​​includes: Based on all the target abnormal items, an abnormal item association map is constructed to analyze the logical dependency and physical impact path between each target abnormal item; Generate an exception handling timeliness parameter and an exception handling intensity parameter for each target exception item according to the exception item association map, the target impact value corresponding to each target exception item, and the preset priority value of the target impact object; An exception handling strategy for the smart cooker is generated according to all the exception handling timeliness parameters and all the exception handling intensity parameters.

[0019] As an optional embodiment, in the second aspect of the present invention, the generation module generates remote control parameters for the smart cooker according to the exception handling strategy, and the specific manner of regulating the smart cooker includes: determining, according to the abnormality handling strategy, a current control mechanism of the intelligent cooker, a target control parameter of the current control mechanism, and an expected control effect parameter of the target control parameter; sensing an environmental state parameter of the target control parameter; Analyzing, according to the environmental state parameters, the simulated control effect parameters of the target control parameters under the environmental state parameters; Calculating a matching value between the expected control effect parameter and the simulated control effect parameter; updating the target control parameter according to the matching value; According to the updated target control parameter and the current control mechanism, remote control parameters of the smart cooker are generated to regulate the smart cooker.

[0020] The third aspect of the present invention discloses another smart cooker remote control and data analysis device based on the Internet of Things, the device comprising: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the remote control and data analysis method of the smart cooker based on the Internet of Things disclosed in the first aspect of the present invention.

[0021] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the remote control and data analysis method of the smart cooker based on the Internet of Things disclosed in the first aspect of the present invention.

[0022] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: In an embodiment of the present invention, when a user-triggered remote control command is received, first usage parameters of the smart cooker within a first time period are obtained; based on the first usage parameters, it is determined whether the smart cooker has at least one abnormal usage item; when it is determined that the smart cooker has at least one abnormal usage item, an abnormality handling strategy for the smart cooker is generated based on all abnormal usage items; and based on the abnormality handling strategy, remote control parameters of the smart cooker are generated to control the smart cooker. It can be seen that the implementation of the present invention can, upon receiving a user-triggered remote control command, trigger active monitoring of the first usage parameter of the smart cooker within a first time period, thereby avoiding reliance on the user to actively report anomalies. Furthermore, when it is determined based on the first usage parameter that the smart cooker has at least one usage anomaly, an exception handling strategy is automatically generated based on all usage anomalies, and the cooker is remotely controlled, reducing the need for manual intervention. This improves the comprehensiveness and accuracy of data analysis for the smart cooker, enhances the safety of use of the smart cooker, and improves the accuracy and efficiency of remote control of the smart cooker. Furthermore, the user can adjust cooker parameters without on-site operation, thereby expanding the practicality of remote control scenarios. Furthermore, based on multidimensional data-driven decision-making and relying on the first usage parameter within the first time period, the objectivity and comprehensiveness of anomaly judgment are improved, encompassing comprehensive detection, analysis, and remote automatic control of both anomalies of the smart cooker itself and abnormal control of the smart cooker by the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 This is a flow chart of a method for remote control and data analysis of an intelligent cooker based on the Internet of Things disclosed in an embodiment of the present invention; Figure 2 This is a flow chart of another method for remote control and data analysis of an intelligent cooker based on the Internet of Things disclosed in an embodiment of the present invention; Figure 3 This is a schematic structural diagram of an IoT-based smart cooker remote control and data analysis device disclosed in an embodiment of the present invention; Figure 4 This is a structural diagram of another smart cooker remote control and data analysis device based on the Internet of Things disclosed in an embodiment of the present invention; Figure 5 This is a structural diagram of another smart cooker remote control and data analysis device based on the Internet of Things disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0026] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different items, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or end comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed therein, or may optionally include other steps or elements inherent to such process, method, product, or end.

[0027] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0028] The present invention discloses a method and device for remote control and data analysis of smart stoves based on the Internet of Things. Upon receiving a user-triggered remote control command, the method and device can trigger active monitoring of a first usage parameter of the smart stove within a first time period, eliminating reliance on users to proactively report anomalies. Furthermore, when at least one abnormal usage item is detected in the smart stove based on the first usage parameter, an abnormality handling strategy is automatically generated based on all abnormal usage items, and the stove is remotely controlled. This reduces the need for manual intervention, improves the comprehensiveness and accuracy of data analysis for the smart stove, enhances the safety of smart stove use, and improves the accuracy and efficiency of remote control of the smart stove. Furthermore, the method and device can adjust stove parameters without on-site operation, expanding the practicality of remote control scenarios. Furthermore, based on multidimensional data-driven decision-making and relying on the first usage parameter within the first time period, the method improves the objectivity and comprehensiveness of abnormality judgment, encompassing comprehensive detection, analysis, and remote automatic control of both abnormalities in the smart stove itself and abnormal user control of the smart stove. These are described in detail below.

[0029] Example 1 See also Figure 1 , Figure 1 This is a flow chart of a method for remote control and data analysis of an intelligent cooker based on the Internet of Things disclosed in an embodiment of the present invention. Figure 1 The described method for remote control and data analysis of smart stoves based on the Internet of Things can be applied to smart stoves, and can also be applied to smart devices including smart stoves and other related smart devices, such smart devices including but not limited to one or more of battery devices, cloud devices, edge computing devices, relay devices, base station devices, city management devices, smart network devices, and smart home devices, which are not limited in the embodiments of the present invention. Figure 1 As shown, the remote control and data analysis method of the smart stove based on the Internet of Things may include the following operations: 101. When a remote control command triggered by a user is received, obtain a first usage parameter of the smart cooker within a first time period; In an embodiment of the present invention, optionally, for receiving remote control commands, the user can send control commands (such as adjusting the firepower, turning off the gas) through the mobile terminal APP or Web interface, and the commands are transmitted to the central controller of the smart stove via the Internet of Things gateway; for obtaining the first usage parameters, the central controller calls modules such as temperature sensors, gas flow meters, and power meters to collect real-time data within the most recent first time period (such as gas flow, heating plate temperature, and power consumption).

[0030] In an embodiment of the present invention, as an optional implementation manner, before obtaining the first usage parameter of the smart cooker within the first time period, the method further includes: Parse the remote control command and obtain the data analysis requirement parameters of the remote control command; According to the data analysis requirement parameter, a target direction parameter of the smart cooker is matched, where the target direction parameter is used to indicate the direction in which the first usage parameter of the smart cooker is obtained; Optionally, the smart cooker includes at least one target module, which is configured to complete a target function corresponding to the smart cooker and obtain a first usage parameter of the smart cooker within a first time period, including: According to the target direction parameter, among all target modules, matching the associated module associated with the target direction parameter; Determine the target sensing range of the smart cooker based on all associated modules; A first usage parameter of the smart cooker within a first time period is obtained according to the target perception range.

[0031] In the embodiment of the present invention, optionally, for remote control command parsing, a natural language processing engine can be deployed on the cloud server to extract the keywords "gas" and "efficiency" as data analysis requirement parameters when parsing the "check gas efficiency" command; For direction parameter matching: In the device feature database, matching is performed on gas-related feature modules, including gas proportional valves, combustion chamber oxygen sensors, and exhaust gas detection modules. Optionally, the target direction parameter may further include a specific geographical location. For related module screening: through the module dependency graph, determine the three core modules included in the gas control subsystem: gas flow meter, ignition device, and pressure sensor; For the definition of sensing scope: the data collection scope is set to include 5 types of parameters of gas-related modules: real-time flow value, cumulative usage, combustion efficiency coefficient, pressure fluctuation value, and ignition success rate; For directional data collection: only the selected gas-related sensors are activated, and data is collected in a 5-second cycle to avoid collecting irrelevant cooling module data; It can be seen that the implementation of this optional embodiment can parse the instruction requirement parameters, match the target direction parameters, and then obtain the perception range data of the associated modules in a targeted manner. The target modules can be targeted and screened through the requirement parameters, thereby reducing redundant data collection, optimizing resource utilization, and improving the accuracy and comprehensiveness of data collection. By realizing dynamic perception range adaptation, the data collection range is dynamically adjusted according to the target direction, thereby enhancing the flexibility of the system and adapting to the needs of different scenarios. By reducing the computing load and only processing the data of the relevant modules, the response time is shortened, and the system processing efficiency is improved. By decoupling the functional modules, that is, isolating the functions through modular design, it is convenient for subsequent functional expansion and maintenance, which is beneficial to improving the comprehensiveness and accuracy of the perception acquisition of the first usage parameters of the smart stove in the first time period, and providing a solid data analysis foundation for the subsequent remote control of the smart stove.

[0032] 102. Determine, based on the first usage parameter, whether the smart cooker has at least one abnormal usage item; In an embodiment of the present invention, optionally, in one embodiment, the collected data is compared with a preset safety threshold (e.g., a gas flow upper limit of 200 L / h, a temperature threshold of 300°C). If the gas flow suddenly increases to 250 L / h and the temperature does not rise synchronously, it is determined to be a gas leakage anomaly; In an embodiment of the present invention, as another optional implementation manner, the first usage parameter includes at least one type of first usage sub-parameter selected from the group consisting of a gas usage parameter, a heating usage parameter, a power usage parameter, a heat dissipation usage parameter, a radiation usage parameter, a usage time parameter, and a usage object parameter. Determining whether the smart cooker has at least one abnormal usage item based on the first usage parameter includes: Determining a second usage parameter of the smart cooker within a second time period based on the data analysis demand parameter, where the second usage parameter corresponds to the first usage parameter; For each type of second usage sub-parameter in the second usage parameters, calculating a usage trajectory baseline parameter range of the second usage sub-parameter of the type according to the second usage sub-parameter of the type within the second time period; For each type of first usage sub-parameter in the first usage parameter, determining whether the first usage sub-parameter of the type is within a range of a usage trajectory reference parameter corresponding to the same type; When it is determined that the first usage sub-parameter of this type is not within the range of the corresponding usage trajectory reference parameter of the same type, the first usage sub-parameter of this type is determined as an abnormal usage item of the smart cooker.

[0033] In the embodiment of the present invention, optionally, for the calculation of the benchmark parameter, the gas usage data of the same time period (19:00-20:00) in the second period can be retrieved, and the benchmark range is calculated to be 150L / h±15% on average, and a normal distribution model is established; For trajectory comparison analysis: When the current gas flow rate monitored in real time is 180L / h (exceeding the average by 20%), and the temperature sensor shows that the heating efficiency has not increased, it is determined to be abnormal consumption; For the multi-dimensional verification mechanism: Synchronous verification of power parameters is performed, and if it is found that the power consumption does not match the gas increase (for example, the power only increases by 5%), it is confirmed that the combustion efficiency is abnormal; For anomaly type annotation: add the "Gas-Efficiency Anomaly" tag to the anomaly database and record characteristic values ​​such as deviation +20% and duration 3 minutes. As can be seen, implementing this optional embodiment enables dynamic determination of whether the first usage parameter deviates from the normal trajectory range based on the baseline parameter of the second time period. Establishing a personalized baseline using historical data from the second time period avoids misjudgments caused by fixed thresholds. By distinguishing anomalies by parameter type (e.g., gas, power, etc.), detection granularity is improved. Anomalies are determined based on the trajectory of parameter changes rather than single point values, enhancing sensitivity to gradual changes. Independent determination of multi-dimensional parameters prevents a single parameter anomaly from masking an overall problem. Ultimately, this improves the adaptability of dynamic baselines, refines anomaly type identification, enables trajectory-based learning, and reduces the risk of missed detections.

[0034] 103. When it is determined that the smart cooker has at least one abnormal usage item, generating an abnormality handling strategy for the smart cooker based on all abnormal usage items; In the embodiment of the present invention, optionally, for example, in response to abnormal gas leakage, a linkage strategy of "closing the solenoid valve + starting exhaust" is generated; In an embodiment of the present invention, as another optional implementation, the above-mentioned generation of an exception handling strategy for the smart cooker based on all abnormal usage items includes: For each abnormal usage item, analyze the preliminary impact objects of the abnormal usage item. The preliminary impact objects are used to represent the conditions of the objects that are associated with the abnormal usage item. Each preliminary impact object has a corresponding target impact value, which is used to represent the degree of impact of the abnormal usage item on the corresponding preliminary impact object. Determine a target impact object among all prepared impact objects based on all target impact values, where all target impact values ​​of the target impact object are greater than or equal to a preset target impact threshold; Among all the abnormal items used, obtain the target abnormal items related to the target impact object; Based on all target abnormal items and their corresponding target impact values, an abnormality handling strategy for the smart stove is generated.

[0035] In the embodiment of the present invention, optionally, the affected objects are modeled: an equipment impact relationship matrix is ​​established, and it is defined that the objects that may be affected by the gas anomaly include: the stove body, the exhaust pipe, environmental safety, and living organisms.

[0036] Regarding impact value calculation: The impact value of environmental safety calculated through a weighted algorithm reached 0.92 (exceeding the threshold of 0.85), and was determined as the primary treatment target; For abnormal item association analysis: In the impact topology diagram, there are three impact paths for gas anomaly association: direct leakage risk, incomplete combustion risk, and equipment overheating risk; For strategy priority sorting: generate a three-level processing strategy: Level 1: immediately shut off the gas (for leaks), Level 2: enhance exhaust (for exhaust gas treatment), Level 3: reduce power (to prevent overheating); It can be seen that the implementation of this optional embodiment can give priority to abnormal items associated with high-impact objects by analyzing the impact value of abnormal items on the prepared impact objects, quantify the severity of abnormal items by impact values, optimize the processing order, improve processing efficiency, and avoid local abnormalities causing chain reactions (such as heat dissipation abnormalities causing equipment damage) by identifying associated impact objects. By focusing on key abnormal items of high-impact objects, resources can be avoided from being wasted on minor issues. By giving priority to resolving abnormal items that directly affect safety (such as gas leaks), accident risks can be reduced, and ultimately problem priority stratification, systemic risk avoidance, resource allocation optimization, and user safety enhancement can be achieved.

[0037] In this optional embodiment, as an optional implementation manner, the above-mentioned target impact value is calculated as follows: Calculate the target distance value between the first usage sub-parameter of the usage exception item and the corresponding usage trajectory reference parameter range of the same type; Sense and use multi-dimensional parameters of the prepared impact object corresponding to the abnormal item, where the multi-dimensional parameters include at least two of attribute parameters, state parameters, age parameters, and configuration parameters; According to the multi-dimensional parameters and the target distance value, the target impact value corresponding to the prepared impact object is calculated.

[0038] In the embodiment of the present invention, optionally, for the deviation calculation: using the standard deviation multiple method, if the current gas value deviates from the benchmark mean by 2.3σ (the preset threshold is 2σ), it is marked as a significant abnormality; For multi-dimensional parameter fusion: collect the exhaust pipe material (stainless steel / 0.8 durability coefficient), service life (3 years / 0.7 attenuation coefficient), and ambient humidity (75% RH) to build an impact model; For dynamic weight adjustment: in humid environments, the corrosion risk factor is given an additional 30% weight, increasing the comprehensive impact value from 0.75 to 0.93; Impact value visualization: The risk level of each impacted object is displayed in the form of a heat map on the operation and maintenance dashboard, and a red warning is displayed in the environmental safety area; It can be seen that the implementation of this optional embodiment can dynamically calculate the impact value by combining the target distance value with multi-dimensional parameters (attributes, status, etc.), avoid single-dimensional misjudgment by fusing parameter deviation (distance value) with equipment status (age, configuration, etc.), dynamically adjust the impact value weight according to different dimensional parameters (such as abnormalities of old equipment have a higher impact), adapt to different usage environments through multi-dimensional parameters (such as differences in power parameters in high-altitude areas), and predict potential risks in combination with equipment status (such as abnormal heat dissipation + old equipment = higher fire risk), thereby achieving comprehensive impact assessment, personalized weight adaptation, cross-scenario compatibility, and dynamic risk prediction.

[0039] In this optional embodiment, as another optional implementation manner, the above-mentioned target impact object includes a corresponding preset priority value, and an exception handling strategy for the smart cooker is generated based on all target abnormal items and their corresponding target impact values, including: Based on all target abnormal items, an abnormal item association map is constructed to analyze the logical dependency and physical impact path between each target abnormal item; Generate exception processing timeliness parameters and exception processing intensity parameters for each target exception item based on the exception item association map, the target impact value corresponding to each target exception item, and the preset priority value of the target impact object; Generate an exception handling strategy for the smart cooker based on all exception handling time parameters and all exception handling intensity parameters.

[0040] In the embodiment of the present invention, for graph construction: the graph database Neo4j is used to establish an abnormal association network, the nodes include: gas valve (ID001), igniter (ID002), and the edge relationship definition is "pressure abnormality → ignition failure"; For timeliness calculation: Based on historical maintenance data, for example, gas anomalies must be responded to within 120 seconds, while electrical anomalies are allowed a 300-second response window; For intensity parameter generation: For example, for a gas leak that lasts for 3 minutes, a disposal plan with intensity level P3 (the highest level) is generated, requiring immediate cutting off of the gas source and activation of the audible and visual alarms; For the strategy optimization engine: Using a reinforcement learning model, after analyzing 1,000 historical disposal records, the optimization concluded that the exhaust intensity during nighttime hours should be increased accordingly; It can be seen that the implementation of this optional embodiment can construct an abnormal item association map, combine the impact value and priority to generate timeliness and intensity parameters, reveal the dependency relationship between abnormal items through the map (such as power abnormality leading to heat dissipation abnormality), avoid isolated processing, ensure rapid response to emergency problems through timeliness parameters, match the processing intensity with intensity parameters (such as gradually reducing power or directly shutting down), balance user needs through priority values ​​(such as reducing power during cooking takes precedence over forced shutdown), reduce the risk of secondary abnormalities by simulating the impact path of the processing strategy based on the map, and ultimately achieve problem correlation analysis, dynamic adjustment of strategies, resource coordination and optimization, and predictability of processing effects.

[0041] 104. Generate remote control parameters of the smart cooker according to the exception handling strategy to control the smart cooker.

[0042] In the embodiment of the present invention, the remote control parameters are optionally executed: for example, a closing instruction code 0x01 is sent to the solenoid valve, and a starting instruction code 0xA0 is sent to the exhaust fan, so as to realize automatic safety control of the stove.

[0043] Optionally, the exception handling strategy can be packaged and one-click repair reporting can be achieved through remote control parameters, so that professional maintenance personnel can come to the site for further maintenance and adjustments.

[0044] It can be seen that the implementation of the embodiments of the present invention can, upon receiving a user-triggered remote control command, trigger active monitoring of the first usage parameter of the smart cooker within a first time period, thereby avoiding reliance on the user to actively report anomalies. Furthermore, when at least one usage anomaly item is determined to exist in the smart cooker based on the first usage parameter, an exception handling strategy is automatically generated based on all usage anomalies, and the cooker is remotely controlled. This reduces the need for manual intervention, improves the comprehensiveness and accuracy of data analysis for the smart cooker, enhances the safety of use of the smart cooker, and improves the accuracy and efficiency of remote control of the smart cooker. Furthermore, the user can adjust cooker parameters without on-site operation, thereby expanding the practicality of remote control scenarios. Furthermore, based on multidimensional data-driven decision-making and relying on the first usage parameter within the first time period, the objectivity and comprehensiveness of anomaly judgment are improved, encompassing comprehensive detection, analysis, and remote automatic control of both anomalies of the smart cooker itself and abnormal control of the smart cooker by the user.

[0045] Example 2 See also Figure 2 , Figure 2 This is a flow chart of another method for remote control and data analysis of smart stoves based on the Internet of Things disclosed in an embodiment of the present invention. Figure 2 The described method for remote control and data analysis of smart stoves based on the Internet of Things can be applied to smart stoves, and can also be applied to smart devices including smart stoves and other related smart devices, such smart devices including but not limited to one or more of battery devices, cloud devices, edge computing devices, relay devices, base station devices, city management devices, smart network devices, and smart home devices, which are not limited in the embodiments of the present invention. Figure 2 As shown, the remote control and data analysis method of the smart stove based on the Internet of Things may include the following operations: 201. When a remote control command triggered by a user is received, obtaining a first usage parameter of the smart cooker within a first time period; 202. Determine, based on the first usage parameter, whether the smart cooker has at least one abnormal usage item; 203. When it is determined that the smart cooker has at least one abnormal usage item, generating an abnormality handling strategy for the smart cooker based on all abnormal usage items; In the embodiment of the present invention, for the supplementary explanation of steps 201 to 203, please refer to the supplementary explanation of steps 101 to 103 in the first embodiment, which will not be described in detail in the embodiment of the present invention.

[0046] 204. Determine, according to the exception handling strategy, a current control mechanism of the intelligent cooker, target control parameters of the current control mechanism, and expected control effect parameters of the target control parameters; 205. Environmental state parameters of the perceived target control parameters; 206. Analyze the simulated control effect parameters of the target control parameters under the environmental state parameters according to the environmental state parameters; 207. Calculate the matching value between the expected control effect parameter and the simulated control effect parameter; 208. Update the target control parameter according to the matching value; 209. Generate remote control parameters of the smart cooker based on the updated target control parameters and the current control mechanism to control the smart cooker.

[0047] In an embodiment of the present invention, the control mechanism can be optionally selected as follows: when dealing with gas anomalies, the electromagnetic shut-off valve is selected as the main control device to assist in controlling the exhaust fan. Other mechanisms and equipment may also be included, such as sound and light equipment, alarm equipment, communication equipment, etc.

[0048] Regarding the environmental compensation mechanism: if it is detected that the current altitude is 1500 meters, the gas pressure setting value will be automatically adjusted from 3kPa to 3.5kPa to compensate for the influence of air density. Furthermore, it can also be based on collaborative compensation analysis of ambient temperature, humidity, air particle distribution, odor, etc.

[0049] For digital twin verification: For example, if the current environmental parameters (temperature 25°C, humidity 60%) are injected into the virtual stove model, the simulation shows that the pressure returns to zero within 3 seconds after the valve is closed.

[0050] For parameter iterative optimization: For example, based on the goodness of fit between the actual pressure drop curve and the simulation curve (R²=0.92), the closing instruction duration was optimized from 500ms to 550ms.

[0051] For command encapsulation transmission: For example, encapsulate the control parameters into MQTT protocol messages, set the highest transmission guarantee level of QoS=2, and ensure execution reliability through dual-channel redundant transmission.

[0052] It can be seen that the implementation of the embodiments of the present invention can further, after generating the abnormality handling strategy of the smart cooker, simulate the control effect after sensing the environmental state parameters, realize dynamic adjustment of the target control parameters, adjust the control parameters according to the real-time environment (such as temperature and humidity), avoid strategy failure (such as changes in heat dissipation requirements in a high-temperature environment), reduce secondary problems caused by blind control by simulating and predicting the strategy effect, iteratively update the parameters based on the matching value, approach the optimal control effect (such as step-by-step adjustment of firepower), tolerate environmental fluctuations (such as voltage instability), and ensure the stability of the control process, ultimately achieving enhanced environmental adaptability, control effect verification, dynamic parameter optimization, and improved robustness of the remote control of the smart cooker.

[0053] Example 3 See also Figure 3 , Figure 3 This is a schematic diagram of the structure of a remote control and data analysis device for smart stoves based on the Internet of Things disclosed in an embodiment of the present invention. The remote control and data analysis device for smart stoves based on the Internet of Things can be applied to smart stoves, and can also be applied to smart devices including smart stoves and other related smart devices. The smart devices include but are not limited to one or more of battery devices, cloud devices, edge computing devices, relay devices, base station devices, city management devices, smart network devices, and smart home devices, which are not limited in the embodiment of the present invention. Figure 3 As shown, the IoT-based smart stove remote control and data analysis device may include: An acquisition module 301 is configured to acquire a first usage parameter of the smart cooker within a first time period upon receiving a remote control instruction triggered by a user; A determination module 302 is configured to determine whether the smart cooker has at least one abnormal usage item based on the first usage parameter; A generating module 303 is configured to generate an exception handling strategy for the smart cooker based on all the abnormal usage items when the judging module 302 determines that the smart cooker has at least one abnormal usage item; The generating module 303 is further configured to generate remote control parameters of the smart cooker according to the exception handling strategy, so as to regulate the smart cooker.

[0054] It can be seen that the implementation of the embodiments of the present invention can, upon receiving a user-triggered remote control command, trigger active monitoring of the first usage parameter of the smart cooker within a first time period, thereby avoiding reliance on the user to actively report anomalies. Furthermore, when at least one usage anomaly item is determined to exist in the smart cooker based on the first usage parameter, an exception handling strategy is automatically generated based on all usage anomalies, and the cooker is remotely controlled. This reduces the need for manual intervention, improves the comprehensiveness and accuracy of data analysis for the smart cooker, enhances the safety of use of the smart cooker, and improves the accuracy and efficiency of remote control of the smart cooker. Furthermore, the user can adjust cooker parameters without on-site operation, thereby expanding the practicality of remote control scenarios. Furthermore, based on multidimensional data-driven decision-making and relying on the first usage parameter within the first time period, the objectivity and comprehensiveness of anomaly judgment are improved, encompassing comprehensive detection, analysis, and remote automatic control of both anomalies of the smart cooker itself and abnormal control of the smart cooker by the user.

[0055] In the embodiment of the present invention, as an optional implementation method, Figure 4 As shown, the device also includes: The parsing module 304 parses the remote control instruction to obtain a data analysis requirement parameter of the remote control instruction before the obtaining module 301 obtains the first usage parameter of the smart cooker in the first time period; A matching module 305 is configured to match a target direction parameter of the smart cooker according to the data analysis requirement parameter, where the target direction parameter is used to indicate a direction for obtaining the first usage parameter of the smart cooker; Optionally, the smart cooker includes at least one target module, which is used to complete a target function corresponding to the smart cooker. The specific manner in which the acquisition module 301 acquires the first usage parameter of the smart cooker within the first time period includes: According to the target direction parameter, among all target modules, matching the associated module associated with the target direction parameter; Determine the target sensing range of the smart cooker based on all associated modules; A first usage parameter of the smart cooker within a first time period is obtained according to the target perception range.

[0056] It can be seen that the implementation of this optional embodiment can parse the instruction requirement parameters, match the target direction parameters, and then obtain the perception range data of the associated modules in a targeted manner. The target modules can be targeted and screened through the requirement parameters, thereby reducing redundant data collection, optimizing resource utilization, and improving the accuracy and comprehensiveness of data collection. By realizing dynamic perception range adaptation, the data collection range is dynamically adjusted according to the target direction, thereby enhancing the flexibility of the system and adapting to the needs of different scenarios. By reducing the computing load and only processing the data of the relevant modules, the response time is shortened, and the system processing efficiency is improved. By decoupling the functional modules, that is, isolating the functions through modular design, it is convenient for subsequent functional expansion and maintenance, which is beneficial to improving the comprehensiveness and accuracy of the perception acquisition of the first usage parameters of the smart stove in the first time period, and providing a solid data analysis foundation for the subsequent remote control of the smart stove.

[0057] In this optional embodiment, as an optional implementation manner, the first usage parameter includes at least one type of first usage sub-parameter selected from the group consisting of a gas usage parameter, a heating usage parameter, a power usage parameter, a heat dissipation usage parameter, a radiation usage parameter, a usage time parameter, and a usage object parameter. The specific manner in which the judgment module 302 judges whether the smart cooker has at least one abnormal usage item based on the first usage parameter includes: Determining a second usage parameter of the smart cooker within a second time period based on the data analysis demand parameter, where the second usage parameter corresponds to the first usage parameter; For each type of second usage sub-parameter in the second usage parameters, calculating a usage trajectory baseline parameter range of the second usage sub-parameter of the type according to the second usage sub-parameter of the type within the second time period; For each type of first usage sub-parameter in the first usage parameter, determining whether the first usage sub-parameter of the type is within a range of a usage trajectory reference parameter corresponding to the same type; When it is determined that the first usage sub-parameter of this type is not within the range of the corresponding usage trajectory reference parameter of the same type, the first usage sub-parameter of this type is determined as an abnormal usage item of the smart cooker.

[0058] As can be seen, implementing this optional embodiment enables dynamic determination of whether the first usage parameter deviates from the normal trajectory range based on the baseline parameter of the second time period. Establishing a personalized baseline using historical data from the second time period avoids misjudgments caused by fixed thresholds. By distinguishing anomalies by parameter type (e.g., gas, power, etc.), detection granularity is improved. Anomalies are determined based on the trajectory of parameter changes rather than single point values, enhancing sensitivity to gradual changes. Independent determination of multi-dimensional parameters prevents a single parameter anomaly from masking an overall problem. Ultimately, this improves the adaptability of dynamic baselines, refines anomaly type identification, enables trajectory-based learning, and reduces the risk of missed detections.

[0059] In the embodiment of the present invention, as another optional implementation, the specific manner in which the above-mentioned generation module 303 generates the exception handling strategy of the smart cooker based on all abnormal usage items includes: For each abnormal usage item, analyze the preliminary impact objects of the abnormal usage item. The preliminary impact objects are used to represent the conditions of the objects that are associated with the abnormal usage item. Each preliminary impact object has a corresponding target impact value, which is used to represent the degree of impact of the abnormal usage item on the corresponding preliminary impact object. Determine a target impact object among all prepared impact objects based on all target impact values, where all target impact values ​​of the target impact object are greater than or equal to a preset target impact threshold; Among all the abnormal items used, obtain the target abnormal items related to the target impact object; Based on all target abnormal items and their corresponding target impact values, an abnormality handling strategy for the smart stove is generated.

[0060] It can be seen that the implementation of this optional embodiment can give priority to abnormal items associated with high-impact objects by analyzing the impact value of abnormal items on the prepared impact objects, quantify the severity of abnormal items by impact values, optimize the processing order, improve processing efficiency, and avoid local abnormalities causing chain reactions (such as heat dissipation abnormalities causing equipment damage) by identifying associated impact objects. By focusing on key abnormal items of high-impact objects, resources can be avoided from being wasted on minor issues. By giving priority to resolving abnormal items that directly affect safety (such as gas leaks), accident risks can be reduced, and ultimately problem priority stratification, systemic risk avoidance, resource allocation optimization, and user safety enhancement can be achieved.

[0061] In this optional embodiment, as an optional implementation manner, the above-mentioned target impact value is calculated as follows: Calculate the target distance value between the first usage sub-parameter of the usage exception item and the corresponding usage trajectory reference parameter range of the same type; Sense and use multi-dimensional parameters of the prepared impact object corresponding to the abnormal item, where the multi-dimensional parameters include at least two of attribute parameters, state parameters, age parameters, and configuration parameters; According to the multi-dimensional parameters and the target distance value, the target impact value corresponding to the prepared impact object is calculated.

[0062] It can be seen that the implementation of this optional embodiment can dynamically calculate the impact value by combining the target distance value with multi-dimensional parameters (attributes, status, etc.), avoid single-dimensional misjudgment by fusing parameter deviation (distance value) with equipment status (age, configuration, etc.), dynamically adjust the impact value weight according to different dimensional parameters (such as abnormalities of old equipment have a higher impact), adapt to different usage environments through multi-dimensional parameters (such as differences in power parameters in high-altitude areas), and predict potential risks in combination with equipment status (such as abnormal heat dissipation + old equipment = higher fire risk), thereby achieving comprehensive impact assessment, personalized weight adaptation, cross-scenario compatibility, and dynamic risk prediction.

[0063] In this optional embodiment, as another optional implementation, the target impact object includes a corresponding preset priority value. The generation module 303 generates an exception handling strategy for the smart cooker based on all target abnormal items and their corresponding target impact values. The specific method includes: Based on all target abnormal items, an abnormal item association map is constructed to analyze the logical dependency and physical impact path between each target abnormal item; Generate exception processing timeliness parameters and exception processing intensity parameters for each target exception item based on the exception item association map, the target impact value corresponding to each target exception item, and the preset priority value of the target impact object; Generate an exception handling strategy for the smart cooker based on all exception handling time parameters and all exception handling intensity parameters.

[0064] It can be seen that the implementation of this optional embodiment can construct an abnormal item association map, combine the impact value and priority to generate timeliness and intensity parameters, reveal the dependency relationship between abnormal items through the map (such as power abnormality leading to heat dissipation abnormality), avoid isolated processing, ensure rapid response to emergency problems through timeliness parameters, match the processing intensity with intensity parameters (such as gradually reducing power or directly shutting down), balance user needs through priority values ​​(such as reducing power during cooking takes precedence over forced shutdown), reduce the risk of secondary abnormalities by simulating the impact path of the processing strategy based on the map, and ultimately achieve problem correlation analysis, dynamic adjustment of strategies, resource coordination and optimization, and predictability of processing effects.

[0065] In an optional embodiment, the specific manner in which the generation module 303 generates the remote control parameters of the smart cooker according to the exception handling strategy includes: Determine, according to the abnormality handling strategy, the current control mechanism of the intelligent cooker, the target control parameters of the current control mechanism, and the expected control effect parameters of the target control parameters; Environmental state parameters of perceived target control parameters; According to the environmental state parameters, analyze the simulated control effect parameters of the target control parameters under the environmental state parameters; Calculating the matching value between the expected control effect parameter and the simulated control effect parameter; According to the matching value, the target control parameters are updated; According to the updated target control parameters and the current control mechanism, the remote control parameters of the smart cooker are generated.

[0066] It can be seen that the implementation of the embodiments of the present invention can further, after generating the abnormality handling strategy of the smart cooker, simulate the control effect after sensing the environmental state parameters, realize dynamic adjustment of the target control parameters, adjust the control parameters according to the real-time environment (such as temperature and humidity), avoid strategy failure (such as changes in heat dissipation requirements in a high-temperature environment), reduce secondary problems caused by blind control by simulating and predicting the strategy effect, iteratively update the parameters based on the matching value, approach the optimal control effect (such as step-by-step adjustment of firepower), tolerate environmental fluctuations (such as voltage instability), and ensure the stability of the control process, ultimately achieving enhanced environmental adaptability, control effect verification, dynamic parameter optimization, and improved robustness of the remote control of the smart cooker.

[0067] Example 4 See also Figure 5 , Figure 5 This is a structural diagram of another smart stove remote control and data analysis device based on the Internet of Things disclosed in an embodiment of the present invention. The smart stove remote control and data analysis device based on the Internet of Things can be applied to smart stoves, and can also be applied to smart devices including smart stoves and other related smart devices. The smart devices include but are not limited to one or more of battery devices, cloud devices, edge computing devices, relay devices, base station devices, city management devices, smart network devices, and smart home devices, which are not limited in the embodiment of the present invention. Figure 5 As shown, the IoT-based smart stove remote control and data analysis device may include: The memory 401 stores executable program codes.

[0068] A processor 402 is coupled to the memory 401 .

[0069] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the method for remote control and data analysis of an intelligent cooker based on the Internet of Things described in the first embodiment or the second embodiment of the present invention.

[0070] Example 5 An embodiment of the present invention discloses a computer storage medium storing computer instructions. When the computer instructions are called, they are used to execute the steps of the method for remote control and data analysis of an intelligent cooker based on the Internet of Things described in Embodiment 1 or Embodiment 2 of the present invention.

[0071] Example 6 An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps of the method for remote control and data analysis of an intelligent cooker based on the Internet of Things described in Example 1 or Example 2.

[0072] The device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Those skilled in the art can understand and implement the present invention without inventive effort.

[0073] Through the detailed description of the above embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disk storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0074] Finally, it should be noted that the method and device for remote control and data analysis of an intelligent cooker based on the Internet of Things disclosed in the embodiments of the present invention only disclose preferred embodiments of the present invention, which are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A remote control and data analysis method for intelligent stoves based on the Internet of Things, characterized in that: The method comprises: When a remote control command triggered by a user is received, obtaining a first usage parameter of the smart cooker within a first time period; determining, based on the first usage parameter, whether the smart cooker has at least one abnormal usage item; When it is determined that the smart cooker has at least one abnormal usage item, generating an abnormality handling strategy for the smart cooker according to all the abnormal usage items; According to the exception handling strategy, remote control parameters of the smart cooker are generated to regulate the smart cooker.

2. The method for remote control and data analysis of an intelligent cooker based on the Internet of Things according to claim 1, characterized in that: Before obtaining the first usage parameter of the smart cooker within the first time period, the method further includes: Parsing the remote control instruction to obtain data analysis requirement parameters of the remote control instruction; matching a target direction parameter of the smart cooker according to the data analysis requirement parameter, where the target direction parameter is used to indicate a direction for obtaining the first usage parameter of the smart cooker; Furthermore, the smart cooker includes at least one target module, and the target module is used to complete a target function corresponding to the smart cooker. The step of obtaining a first usage parameter of the smart cooker within a first time period includes: According to the target direction parameter, matching the associated module associated with the target direction parameter among all the target modules; Determining a target sensing range of the smart cooker based on all the associated modules; A first usage parameter of the smart cooker within a first time period is acquired according to the target sensing range.

3. The method for remote control and data analysis of an intelligent cooker based on the Internet of Things according to claim 2, characterized in that: The first usage parameter includes at least one type of first usage sub-parameter selected from gas usage parameters, heating usage parameters, power usage parameters, heat dissipation usage parameters, radiation usage parameters, usage time parameters, and usage object parameters. The determining, based on the first usage parameters, whether the smart cooker has at least one abnormal usage item includes: determining, according to the data analysis requirement parameter, a second usage parameter of the smart cooker within a second time period, where the second usage parameter corresponds to the first usage parameter; For each type of second usage sub-parameter in the second usage parameter, calculating a usage trajectory reference parameter range of the second usage sub-parameter of the type according to the second usage sub-parameter of the type within the second time period; For each type of first usage sub-parameter in the first usage parameter, determining whether the first usage sub-parameter of the type is within the usage trajectory reference parameter range of the corresponding same type; When it is determined that the first usage sub-parameter of this type is not within the usage trajectory reference parameter range corresponding to the same type, the first usage sub-parameter of this type is determined as an abnormal usage item of the smart cooker.

4. The method for remote control and data analysis of an intelligent cooker based on the Internet of Things according to any one of claims 1 to 3, characterized in that: Generating an exception handling strategy for the smart cooker based on all the abnormal usage items includes: For each abnormal usage item, analyzing a preliminary impact object of the abnormal usage item, wherein the preliminary impact object is used to indicate the status of an object that is associated with and affected by the abnormal usage item, and each preliminary impact object has a corresponding target impact value, which is used to indicate the degree of impact of the abnormal usage item on the corresponding preliminary impact object; Determine a target influence object among all prepared influence objects according to all the target influence values, wherein all the target influence values ​​of the target influence object are greater than or equal to a preset target influence threshold; Obtaining target abnormal items related to the target impact object from among all the abnormal usage items; An exception handling strategy for the smart cooker is generated based on all the target exception items and their corresponding target impact values.

5. The method for remote control and data analysis of an intelligent cooker based on the Internet of Things according to claim 4, characterized in that: The target impact value is calculated as follows: Calculating a target distance value between the first usage sub-parameter of the usage abnormality item and the usage trajectory reference parameter range corresponding to the same type; sensing multi-dimensional parameters of the prepared impact object corresponding to the abnormal usage item, wherein the multi-dimensional parameters include at least two of attribute parameters, state parameters, age parameters, and configuration parameters; Calculate the target impact value corresponding to the prepared impact object according to the multi-dimensional parameter and the target distance value.

6. The method for remote control and data analysis of an intelligent cooker based on the Internet of Things according to claim 5, characterized in that: The target impact object includes a corresponding preset priority value. The abnormality handling strategy of the smart cooker is generated according to all the target abnormal items and their corresponding target impact values, including: Based on all the target abnormal items, an abnormal item association map is constructed to analyze the logical dependency and physical impact path between each target abnormal item; Generate an exception handling timeliness parameter and an exception handling intensity parameter for each target exception item according to the exception item association map, the target impact value corresponding to each target exception item, and the preset priority value of the target impact object; An exception handling strategy for the smart cooker is generated according to all the exception handling timeliness parameters and all the exception handling intensity parameters.

7. The method for remote control and data analysis of an intelligent cooker based on the Internet of Things according to any one of claims 1-3, 5, and 6, characterized in that: Generating remote control parameters of the smart cooker according to the exception handling strategy to regulate the smart cooker includes: determining, according to the abnormality handling strategy, a current control mechanism of the intelligent cooker, a target control parameter of the current control mechanism, and an expected control effect parameter of the target control parameter; sensing an environmental state parameter of the target control parameter; Analyzing, according to the environmental state parameters, the simulated control effect parameters of the target control parameters under the environmental state parameters; Calculating a matching value between the expected control effect parameter and the simulated control effect parameter; updating the target control parameter according to the matching value; According to the updated target control parameter and the current control mechanism, remote control parameters of the smart cooker are generated to regulate the smart cooker.

8. An intelligent stove remote control and data analysis device based on the Internet of Things, characterized in that: The device comprises: an acquisition module, configured to acquire a first usage parameter of the smart cooker within a first time period upon receiving a remote control instruction triggered by a user; a judgment module, configured to judge whether the smart cooker has at least one abnormal usage item according to the first usage parameter; a generating module, configured to generate an abnormality handling strategy for the smart cooker based on all the abnormal usage items when the judging module determines that the smart cooker has at least one abnormal usage item; The generating module is further configured to generate remote control parameters of the smart cooker according to the exception handling strategy, so as to regulate the smart cooker.

9. An intelligent stove remote control and data analysis device based on the Internet of Things, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the remote control and data analysis method of the smart cooker based on the Internet of Things as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that The computer storage medium stores computer instructions, which, when called, are used to execute the remote control and data analysis method for an intelligent cooker based on the Internet of Things as described in any one of claims 1 to 7.

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