Business monitoring method, device and equipment of intelligent kitchen appliance system and storage medium
Through the BCP perspective monitoring middleware, the business layer and data middle platform of the intelligent kitchen appliance system are uniformly monitored, which solves the problem of dispersed monitoring logic in the existing technology, achieves coverage of all key points and abnormal alarms, and improves the stability and security of the system.
Patent Information
- Application Number
- CN202510430931.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-07
- Publication Date
- 2025-08-08
AI Technical Summary
The monitoring methods of existing smart kitchen appliance systems are limited to specific operations or events, and it is difficult to cover all key points of the system, resulting in dispersed monitoring logic and reducing the applicability of the solution.
BCP perspective monitoring middleware is used to determine the target monitoring slices, number of slices and definition information, perform monitoring slices and determine abnormal alarms, realize full key point monitoring of the business layer and data middle platform, and uniformly manage all monitoring sections.
It improves the applicability and efficiency of monitoring, ensures the stability and safety of smart kitchen appliance systems, and can promptly detect and deal with potential safety hazards.
Smart Images
Figure CN120455187A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the field of smart home appliance technology, and specifically relates to a business monitoring method, device, equipment and storage medium for a smart kitchen appliance system. Background Art
[0002] With the rapid development of smart home technology, smart kitchen appliances, such as smart ovens, smart microwaves, and smart rice cookers, have gradually entered thousands of households, providing users with a convenient cooking experience. However, the widespread use of smart kitchen appliances also brings safety risks, such as equipment failure and fires caused by improper operation. To ensure user safety, manufacturers provide a smart kitchen appliance system that monitors user device operating data in real time and issues timely monitoring and alarms. In addition, back-end maintenance personnel can use this system to maintain and manage data, ensuring system stability and security.
[0003] The smart kitchen appliance system monitors the safety of smart kitchen appliance operation by: conducting business and operation monitoring through interceptors, or by adding information such as operators and operation time to the business to conduct business monitoring.
[0004] However, interceptor-based monitoring is usually limited to specific operations or events, making it difficult to cover all key points of the system. Monitoring operations in business logic are often scattered across various modules of the system, making it impossible to uniformly manage monitoring logic and reducing the applicability of the solution. Summary of the Invention
[0005] The present application provides a business monitoring method, device, equipment and storage medium for a smart kitchen appliance system.
[0006] In a first aspect, the present application provides a business monitoring method for a smart kitchen appliance system, which is applied to a BCP perspective monitoring middleware. The BCP perspective monitoring middleware is provided in the smart kitchen appliance system and is used to monitor data transmitted between a data middle platform and a business layer of the smart kitchen appliance system. The method includes:
[0007] Determine a triggered target monitoring slice from a plurality of predefined monitoring slices according to the transmission data of the business layer and the data middle platform, wherein each monitoring slice is used to determine whether the corresponding monitored scenario is operating normally;
[0008] Determining the number of slices of the target monitoring slice and definition information of each target monitoring slice;
[0009] Execute the target monitoring slice according to the number of slices and definition information of each target monitoring slice, and determine whether to trigger an abnormality alarm;
[0010] If an abnormal alarm is triggered, the abnormal monitoring slice is determined, and an alarm operation is performed according to the definition information of the abnormal monitoring slice.
[0011] In a possible implementation, executing the target monitoring slices according to the number of slices and definition information of each target monitoring slice, and determining whether to trigger an abnormality alarm includes:
[0012] If the number of slices is 1, the target monitoring slice is executed according to the definition information, and monitoring is performed to determine whether an abnormal alarm is triggered;
[0013] If the number of slices is greater than 1, the priority of each target monitoring slice is determined, and the execution order of each target monitoring slice is determined in descending order of priority;
[0014] According to the execution order and the definition information of each target monitoring slice, the target monitoring slice is executed, and whether an abnormal alarm is triggered is monitored.
[0015] In a possible implementation, the definition information includes a collection rule and at least one alarm rule, and executing the target monitoring slice according to the definition information and monitoring whether an abnormality alarm is triggered includes:
[0016] Based on the collection rule, determining at least one parameter item to be monitored and a corresponding value from the transmitted data;
[0017] Determining a target alarm rule corresponding to each parameter item to be monitored from at least one alarm rule;
[0018] Whether to trigger an abnormal alarm is determined based on the result of whether the value corresponding to the parameter item to be monitored triggers the corresponding target alarm rule.
[0019] In a possible implementation, performing an alarm operation according to the definition information of the abnormal monitoring slice includes:
[0020] Determining a triggered alarm rule and a corresponding alarm operation from at least one alarm rule in the definition information;
[0021] Execute the alarm operation and update the alarm count;
[0022] When the updated alarm number is greater than or equal to the alarm number threshold, abnormal prompt information is generated and output based on the record corresponding to each abnormal alarm, wherein the abnormal prompt information is used to prompt the user to verify and adjust the triggered alarm rules, or the execution steps of the corresponding monitored scene.
[0023] In a possible implementation, the definition information further includes an interception rule, and the determining of the triggered target monitoring slice from the predefined multiple monitoring slices according to the transmission data of the business layer and the data middle station includes:
[0024] Determine the definition information of each monitoring slice and obtain the interception rules of the corresponding monitoring slice from each definition information;
[0025] determining, according to the transmission data, a target interception rule to be triggered from a plurality of interception rules;
[0026] According to the monitoring slice corresponding to the target interception rule, the triggered target monitoring slice is determined.
[0027] In a possible implementation, before determining the triggered target monitoring slice from the predefined plurality of monitoring slices, the method further includes:
[0028] Determine, based on the functional modules of the business layer and the data middle platform, multiple scenarios to be monitored and at least one anomaly monitoring rule corresponding to each scenario to be monitored;
[0029] For each scene to be monitored, an initial monitoring slice is created according to at least one abnormality monitoring rule corresponding to the scene to be monitored, and the initial monitoring slice is defined to obtain a corresponding monitoring slice.
[0030] In a possible implementation, creating an initial monitoring slice according to at least one abnormality monitoring rule corresponding to the scene to be monitored, and defining the initial monitoring slice to obtain a corresponding monitoring slice includes:
[0031] Creating an initial monitoring slice of the scene to be monitored;
[0032] Extracting a parameter item to be monitored, an allowable value range of the parameter item to be monitored, and an alarm operation from each abnormality monitoring rule;
[0033] Determine corresponding collection rules and at least one alarm rule according to at least one parameter item to be monitored, an allowable value range of each parameter item to be monitored, and an alarm operation;
[0034] Determining an interception rule that triggers the scene to be monitored, and determining definition information based on the interception rule, the collection rule, and the at least one alarm rule;
[0035] A definition operation is performed on the initial monitoring slice according to the definition information to obtain a corresponding monitoring slice.
[0036] In a second aspect, the present application provides a business monitoring device for a smart kitchen appliance system, which is applied to a BCP perspective monitoring middleware. The BCP perspective monitoring middleware is set in the smart kitchen appliance system and is used to monitor data transmitted between the data middle platform and the business layer of the smart kitchen appliance system, including: an information determination module, an anomaly determination module, and an anomaly handling module, wherein:
[0037] The information determination module is used to determine a triggered target monitoring slice from a plurality of predefined monitoring slices based on the transmission data of the business layer and the data middle platform, wherein each monitoring slice is used to determine whether the corresponding monitored scenario is operating normally;
[0038] The information determination module is further used to determine the number of slices of the target monitoring slice and the definition information of each target monitoring slice;
[0039] The abnormality determination module is used to execute the target monitoring slice according to the number of slices and the definition information of each target monitoring slice, and determine whether to trigger an abnormality alarm;
[0040] The exception handling module is used to determine the abnormal monitoring slice if an abnormal alarm is triggered, and perform an alarm operation according to the definition information of the abnormal monitoring slice.
[0041] In a possible implementation, the abnormality determination module is further configured to:
[0042] If the number of slices is 1, the target monitoring slice is executed according to the definition information, and monitoring is performed to determine whether an abnormal alarm is triggered;
[0043] If the number of slices is greater than 1, the priority of each target monitoring slice is determined, and the execution order of each target monitoring slice is determined in descending order of priority;
[0044] According to the execution order and the definition information of each target monitoring slice, the target monitoring slice is executed, and whether an abnormal alarm is triggered is monitored.
[0045] In a possible implementation, the abnormality determination module is further configured to:
[0046] Based on the collection rule, determining at least one parameter item to be monitored and a corresponding value from the transmission data;
[0047] Determining a target alarm rule corresponding to each parameter item to be monitored from at least one alarm rule;
[0048] Whether to trigger an abnormal alarm is determined based on the result of whether the value corresponding to the parameter item to be monitored triggers the corresponding target alarm rule.
[0049] In a possible implementation, the exception handling module is further configured to:
[0050] Determining a triggered alarm rule and a corresponding alarm operation from at least one alarm rule in the definition information;
[0051] Execute the alarm operation and update the alarm count;
[0052] When the updated alarm number is greater than or equal to the alarm number threshold, abnormal prompt information is generated and output based on the record corresponding to each abnormal alarm, wherein the abnormal prompt information is used to prompt the user to verify and adjust the triggered alarm rules, or the execution steps of the corresponding monitored scene.
[0053] In a possible implementation, the information determination module is further configured to:
[0054] Determine the definition information of each monitoring slice and obtain the interception rules of the corresponding monitoring slice from each definition information;
[0055] determining, according to the transmission data, a target interception rule to be triggered from a plurality of interception rules;
[0056] According to the monitoring slice corresponding to the target interception rule, the triggered target monitoring slice is determined.
[0057] In a possible implementation, the information determination module is further configured to:
[0058] Determine, based on the functional modules of the business layer and the data middle platform, multiple scenarios to be monitored and at least one anomaly monitoring rule corresponding to each scenario to be monitored;
[0059] For each scene to be monitored, an initial monitoring slice is created according to at least one abnormality monitoring rule corresponding to the scene to be monitored, and the initial monitoring slice is defined to obtain a corresponding monitoring slice.
[0060] In a possible implementation, the information determination module is further configured to:
[0061] Creating an initial monitoring slice of the scene to be monitored;
[0062] Extracting a parameter item to be monitored, an allowable value range of the parameter item to be monitored, and an alarm operation from each abnormality monitoring rule;
[0063] Determine corresponding collection rules and at least one alarm rule according to at least one parameter item to be monitored, an allowable value range of each parameter item to be monitored, and an alarm operation;
[0064] Determining an interception rule that triggers the scene to be monitored, and determining definition information based on the interception rule, the collection rule, and the at least one alarm rule;
[0065] A definition operation is performed on the initial monitoring slice according to the definition information to obtain a corresponding monitoring slice.
[0066] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;
[0067] The memory stores computer-executable instructions;
[0068] The processor executes the computer-executable instructions stored in the memory to implement the business monitoring method of the smart kitchen appliance system as described in the first aspect.
[0069] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a computer, they are used to implement the business monitoring method of the smart kitchen appliance system as described in the first aspect.
[0070] In a fifth aspect, the present application also provides a computer program product, including a computer program, which, when executed by a processor, can implement the steps of the solution recommendation method as described in any one of the first aspects.
[0071] The business monitoring method, device, equipment and storage medium of the smart kitchen appliance system provided by the present application, the BCP perspective monitoring middleware determines the target monitoring slice, the number of slices of the target monitoring slice and the definition information of each target monitoring slice based on the transmission data of the business layer and the data center. According to the number of slices and the definition information, the target monitoring slice is executed and it is determined whether there is an abnormal alarm. When there is an abnormal alarm, the alarm operation is executed according to the definition information of the abnormal monitoring slice that triggered the abnormal alarm. In the above manner, the BCP perspective monitoring middleware can monitor all key points of the business layer and the data center, and uniformly manage all monitoring aspects to improve the applicability of the solution. BRIEF DESCRIPTION OF THE DRAWINGS
[0072] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.
[0073] Figure 1 A schematic diagram of a scenario provided in an embodiment of the present application;
[0074] Figure 2 A schematic diagram of a business monitoring method for a smart kitchen appliance system provided in an embodiment of the present application Figure 1 ;
[0075] Figure 3 A schematic diagram of a business monitoring method for a smart kitchen appliance system provided in an embodiment of the present application Figure 2 ;
[0076] Figure 4 A schematic diagram of a business monitoring method for a smart kitchen appliance system provided in an embodiment of the present application Figure 3 ;
[0077] Figure 5 A schematic diagram of the structure of a business monitoring device for a smart kitchen appliance system provided in an embodiment of the present application;
[0078] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.
[0079] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION
[0080] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.
[0081] With the rapid development of smart home technology, smart kitchen appliances such as smart ovens, microwave ovens, and rice cookers are becoming increasingly popular, providing users with a convenient cooking experience. However, their widespread use also poses safety risks, such as fires caused by equipment failure or improper operation. To ensure user safety, manufacturers provide a smart kitchen appliance system that monitors device operating data in real time and issues prompt alerts. Furthermore, backend maintenance personnel can use this system to manage and maintain data, ensuring system stability and security. This system monitors services using interceptors or information such as operator and time in the business logic. However, interceptors have a limited monitoring range, and monitoring operations in the business logic are dispersed across various modules, making unified management of the monitoring logic difficult and reducing the solution's applicability.
[0082] The present application provides a business monitoring method for a smart kitchen appliance system. The BCP perspective monitoring middleware determines the target monitoring slice, the number of slices of the target monitoring slice, and the definition information of each target monitoring slice based on the transmission data of the business layer and the data center. According to the number of slices and the definition information, the target monitoring slice is executed and it is determined whether there is an abnormal alarm. When there is an abnormal alarm, the alarm operation is executed according to the definition information of the abnormal monitoring slice that triggered the abnormal alarm. In the above manner, the BCP perspective monitoring middleware can monitor all key points of the business layer and the data center, and uniformly manage all monitoring aspects to improve the applicability of the solution.
[0083] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can exist independently or in combination with each other. For the same or similar concepts or processes, they may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.
[0084] Figure 1 A schematic diagram of a scenario provided in an embodiment of the present application. Figure 1 As shown, the BCP perspective monitoring middleware is deployed in the smart kitchen appliance system. It can transmit data with the business layer and data center of the smart kitchen appliance system, and monitor the operation of the functional modules of the business layer and data center based on the transmitted data.
[0085] The business layer of the smart kitchen appliance system is the core module for user-system interaction. It provides users with a variety of services based on smart kitchen appliances, such as recipe recommendations, cooking mode selection, remote control, and ingredient management. Through an intuitive user interface and intelligent algorithms, the business layer provides users with an efficient and convenient kitchen experience. Meanwhile, the data center, serving as the system's data hub, is responsible for data collection, storage, processing, and analysis. It provides data support for the business layer, such as user behavior analysis, device operating status monitoring, and energy consumption statistics. It also provides back-end operations personnel with tools for system maintenance and troubleshooting.
[0086] The BCP Perspective Monitoring Middleware builds multiple monitoring slices based on the functional modules of the business layer and the data center. Each monitoring slice corresponds to a specific scenario to be monitored. Based on the data transmitted between the data center and the business layer, the BCP Perspective Monitoring Middleware determines whether to trigger a monitoring slice. When a monitoring slice is triggered, it executes it according to its definition to monitor the operation of the corresponding scenario. Furthermore, the data generated by the triggered monitoring slice based on the definition is transferred to the database for storage.
[0087] Figure 2A schematic diagram of a business monitoring method for a smart kitchen appliance system provided in an embodiment of the present application Figure 1 .like Figure 2 As shown, the method includes:
[0088] S201. According to the transmission data of the business layer and the data middle platform, determine the triggered target monitoring slice from multiple predefined monitoring slices.
[0089] In this step, with the rapid development of smart home technology, smart kitchen appliances, such as smart ovens, smart microwaves, and smart rice cookers, have gradually entered thousands of households, providing users with a convenient cooking experience. However, the widespread use of smart kitchen appliances also brings safety risks, such as equipment failure and fires caused by improper operation. To ensure user safety, manufacturers provide a smart kitchen appliance system that can monitor operating data in real time while users are using the devices and issue timely monitoring alarms. In addition, backend maintenance personnel can maintain and manage data based on this system to ensure system stability and security. Smart kitchen appliance systems monitor the operational safety of smart kitchen appliances by using interceptors to monitor business operations and operations, or by adding information such as operator and operation time to the business operations for business monitoring. However, interceptor-based monitoring is often limited to specific operations or events and cannot cover all key points of the system. Monitoring operations in the business logic are often scattered across various modules of the system, resulting in the inability to uniformly manage the monitoring logic and reducing the applicability of the solution.
[0090] Therefore, this embodiment uses the monitoring slices created by the BCP perspective monitoring middleware to monitor the data transmitted by the business layer and the data middle platform of the smart kitchen appliance system to determine whether the functional modules transmitted by the business layer and the data middle platform are executing normally. In other words, the triggered target monitoring slice is determined from multiple predefined monitoring slices based on the data sent by the business layer and the data middle platform. The specific implementation method is as follows:
[0091] Determine the definition information of each monitoring slice and obtain the interception rules of the corresponding monitoring slice from each definition information;
[0092] determining, according to the transmission data, a target interception rule to be triggered from a plurality of interception rules;
[0093] According to the monitoring slice corresponding to the target interception rule, the triggered target monitoring slice is determined.
[0094] S202: Determine the number of target monitoring slices and definition information of each target monitoring slice.
[0095] In this step, in order to ensure the safety of users using smart kitchen appliances, similar to the fire alarm monitoring scenario, as long as the monitoring slice related to the operation of the smart kitchen appliance is triggered, the slice corresponding to the fire alarm monitoring scenario will also be triggered at the same time. At the same time, for some monitoring scenarios with complex functions and large amounts of data, such as monitoring multi-dimensional data during the cooking process, in order to ensure the efficiency and real-time performance of monitoring, the system will adopt multi-slice monitoring technology. That is, the monitoring task is divided into multiple independent monitoring slices, and each slice is responsible for collecting and analyzing data of a specific dimension, such as temperature changes, power consumption, food status, etc. Therefore, the transmission data of the business layer and the data middle platform may trigger multiple target monitoring slices at the same time.
[0096] Furthermore, when there are multiple target monitoring slices triggered in the system, the execution of the slices may present the following two modes:
[0097] Concurrent execution: In some scenarios, multiple target monitoring slices may be executed simultaneously. For example, during a cooking process, the fire alarm monitoring slice and the cooking monitoring slice are activated simultaneously, respectively monitoring whether the device temperature exceeds the safety threshold and whether the cooking parameters meet the preset conditions.
[0098] Sequential execution: In other scenarios, the triggering of target monitoring slices may occur in a certain order. For example, when a device starts up, the system may trigger the security monitoring slice first, and then start the functional monitoring slice after confirming that the device operating environment is normal.
[0099] Therefore, when executing target monitoring slices, it is necessary to combine the number of slices of the target monitoring slices and the definition information of each target monitoring slice to execute the target monitoring slices.
[0100] Therefore, before executing target monitoring slices, it is necessary to determine the number of slices of the target monitoring slices and the slice definition of each target monitoring slice.
[0101] S203: Execute target monitoring slices according to the number of slices and definition information of each target monitoring slice, and determine whether to trigger an abnormal alarm.
[0102] In this step, when it is determined that the number of slices of the target monitoring slice is 1, the target monitoring slice is executed directly according to the slice definition; when it is determined that the number of slices of the target monitoring slice is greater than 1, the execution order of each target monitoring slice is determined, and the target monitoring slice is executed according to the execution order and the slice definition of each target monitoring slice.
[0103] At the same time, in the process of executing each target monitoring slice, according to the definition information of the target monitoring slice, it is determined whether the monitored scene corresponding to the target monitoring slice is operating normally, that is, whether an abnormal alarm is triggered according to the monitored parameter items collected by the target monitoring slice.
[0104] S204: If an abnormal alarm is triggered, the abnormal monitoring slice is determined, and an alarm operation is performed according to the definition information of the abnormal monitoring slice.
[0105] In this step, when an abnormal alarm is triggered according to the definition information during the execution of the target monitoring slice, the corresponding alarm operation needs to be executed according to the definition information. At the same time, considering that the abnormal alarm is triggered based on at least one alarm rule in the definition information, if the number of alarms in the target monitoring slice is high, there is a risk that the alarm rules are set improperly, so the user needs to be prompted to verify the alarm rules.
[0106] Furthermore, the target monitoring slice is used to determine whether the corresponding monitored scene is operating normally. Therefore, when the number of abnormal alarms triggered is high, there is a risk that the execution logic in the corresponding monitored scene is unreasonable, and the user needs to be prompted to verify and adjust it.
[0107] Therefore, when determining that an abnormal alarm is triggered, this embodiment not only executes the corresponding alarm operation, but also executes corresponding measures based on the number of alarms. The specific implementation method is:
[0108] Determining a triggered alarm rule and a corresponding alarm operation from at least one alarm rule in the definition information;
[0109] Execute the alarm operation and update the alarm count;
[0110] When the updated alarm number is greater than or equal to the alarm number threshold, abnormal prompt information is generated and output based on the record corresponding to each abnormal alarm, wherein the abnormal prompt information is used to prompt the user to verify and adjust the triggered alarm rules, or the execution steps of the corresponding monitored scene.
[0111] The alarm threshold can be 4 to 6 times.
[0112] The present application provides a business monitoring method for a smart kitchen appliance system. The BCP perspective monitoring middleware determines the target monitoring slice, the number of slices of the target monitoring slice, and the definition information of each target monitoring slice based on the transmission data of the business layer and the data center. According to the number of slices and the definition information, the target monitoring slice is executed and it is determined whether there is an abnormal alarm. When there is an abnormal alarm, the alarm operation is executed according to the definition information of the abnormal monitoring slice that triggers the abnormal alarm. In the above manner, the BCP perspective monitoring middleware can monitor all key points of the business layer and the data center, and uniformly manage all monitoring aspects, thereby improving the applicability of the solution. At the same time, the multi-slice monitoring technology improves the monitoring efficiency.
[0113] Figure 3 A schematic diagram of a business monitoring method for a smart kitchen appliance system provided in an embodiment of the present application Figure 2 This embodiment describes in detail how to execute target monitoring slices and the steps of determining whether to trigger monitoring anomalies. Figure 3 As shown, the method includes:
[0114] S301: Determine the size relationship between the number of slices and 1.
[0115] In this step, if the number of slices is 1, the target monitoring slice is directly executed according to the definition information. If the number of slices is greater than 1, the execution order of each target monitoring slice is determined, and the target monitoring slice is executed according to the execution order and definition information. Therefore, before executing the target monitoring slice, it is necessary to determine the size relationship between the number of slices and 1.
[0116] S302: If the number of slices is 1, determine at least one parameter item to be monitored and a corresponding value from the transmitted data based on the acquisition rule.
[0117] In this step, if the number of slices is determined to be 1, the collection rules in the definition information are used to directly determine at least one parameter item to be monitored from the transmitted data, as well as the corresponding value of each parameter item to be monitored. This value is used to determine whether to trigger an abnormality alarm based on the alarm rules.
[0118] S303: Determine a target alarm rule corresponding to each parameter item to be monitored from at least one alarm rule.
[0119] In this step, when the parameter items to be monitored and the corresponding values are obtained according to the collection rules, a corresponding target alarm rule is matched to each parameter item to be monitored based on at least one alarm rule in the definition information.
[0120] S304: Determine whether to trigger an abnormal alarm based on the result of whether the value corresponding to the parameter item to be monitored triggers the corresponding target alarm rule.
[0121] In this step, when each monitored parameter item matches the corresponding target alarm rule, the corresponding target alarm rule is determined based on the corresponding value of each monitored parameter item. Furthermore, based on the triggering result of the target alarm rule, it is determined whether an exception alarm is triggered. In other words, if the target alarm rule is triggered, an exception alarm is triggered.
[0122] S305: If the number of slices is greater than 1, determine the priority of each target monitoring slice, and determine the execution order of each target monitoring slice in descending order of priority.
[0123] In this step, when the number of slices of the target monitoring slice is determined to be greater than 1, it indicates that the execution order of each target monitoring slice needs to be determined. The execution order is determined according to a predefined priority.
[0124] Specifically, the priority of each target monitoring slice is obtained, and multiple priorities are sorted in descending order. According to the sorting position of each priority, the execution order of the corresponding target monitoring slice is determined. The same priority has the same corresponding execution order.
[0125] S306. Execute the target monitoring slice according to the execution order and the definition information of each target monitoring slice, and monitor whether an abnormal alarm is triggered.
[0126] In this step, the target monitoring slice to be executed is obtained from multiple target monitoring slices in the execution order. Then, according to the definition information of the target monitoring slice to be executed, the target monitoring slice is executed and the abnormal alarm is detected. The specific execution process and the process of determining the abnormal alarm have been described in detail in the previous steps and will not be further explained here.
[0127] The present application provides a business monitoring method for a smart kitchen appliance system. According to the number of slices being 1 or greater than 1, the parameter items to be monitored, the corresponding numerical values, and the matching target alarm rules are directly determined according to the definition information, and whether an abnormal alarm is triggered is determined according to whether the numerical values trigger the results of the corresponding target alarm rules. Alternatively, the execution order is determined according to the priority of each target monitoring slice, and the target monitoring slice is executed according to the execution order and the definition information. In the above manner, each target monitoring slice is executed and it is determined whether an abnormal alarm is triggered, thereby ensuring the smooth execution of the monitoring of the business layer and the data middle platform of the smart kitchen appliance system and improving the user experience.
[0128] Figure 4 A schematic diagram of a business monitoring method for a smart kitchen appliance system provided in an embodiment of the present application Figure 3 This embodiment describes in detail how to build monitoring slices based on the business layer and data center. Figure 4 As shown, the method includes:
[0129] S401. Determine multiple scenarios to be monitored and at least one abnormal monitoring rule corresponding to each scenario to be monitored based on the functional modules of the business layer and the data middle platform.
[0130] In this step, the business layer of the smart kitchen appliance system is the core module for user-system interaction. It provides users with a variety of services based on smart kitchen appliances, such as recipe recommendations, cooking mode selection, remote control, and ingredient management. The business layer delivers an efficient and convenient kitchen experience through an intuitive user interface and intelligent algorithms. Meanwhile, the data center, serving as the system's data hub, is responsible for data collection, storage, processing, and analysis. It provides data support for the business layer, such as user behavior analysis, device operating status monitoring, and energy consumption statistics. It also provides backend operations personnel with tools for system maintenance and troubleshooting.
[0131] To ensure the operational security and business stability of the smart kitchen appliance system, comprehensive monitoring of data transmission and processing between the business layer and the data center is essential. This prevents anomalies in the business layer and data center, such as data loss, transmission delays, and device failures, from impacting user experience and even posing security risks. Therefore, this embodiment creates monitoring slices based on the functional modules of the business layer and data center.
[0132] Specifically, the business layer is primarily responsible for user interactions with smart kitchen appliances, such as executing user commands, recommending recipes, and selecting cooking modes. The data middle platform, on the other hand, handles data collection, storage, analysis, and transmission, including device operational status monitoring and user behavior data analysis. Based on these two functional modules, the system first identifies key scenarios that could impact system operation and user experience, such as user command execution, device operational status, data transmission integrity, and abnormal behavior monitoring. For each scenario to be monitored, specific anomaly detection rules are developed based on actual business needs and security risks. For example, in the user command execution scenario, a rule might be established: "If the command execution time exceeds 10 seconds or returns a failure status, an anomaly is detected and an alarm is triggered." In the device operational status scenario, a rule might be established: "If the device's temperature, pressure, or energy consumption exceeds a preset safety range, an anomaly alert is generated." In the data transmission integrity scenario, a rule might be established: "If the data transmission loss rate between the business layer and the data middle platform exceeds 1%, an anomaly is detected and a data repair mechanism is initiated."
[0133] S402: Create an initial monitoring slice of the scene to be monitored.
[0134] In this step, after determining multiple scenarios to be monitored and at least one abnormal monitoring rule for each scenario to be monitored based on the functional modules of the business layer and the data middle platform, an initial monitoring slice for each scenario to be monitored is created.
[0135] S403: extracting the parameter item to be monitored, the allowed value range of the parameter item to be monitored, and the alarm operation from each abnormality monitoring rule.
[0136] In this step, the monitoring slice for each monitored scenario in the smart kitchen appliance system is a key tool for ensuring stable system operation. By extracting typical data from the monitored scenario, the monitoring slice reflects the execution status of the scenario in real time, thereby determining whether any anomalies exist. To ensure the effectiveness of the monitoring slice and provide reliable real-time monitoring and early warning capabilities for system operation, it is necessary to define and operate anomaly detection rules based on the monitored scenario.
[0137] Specifically, each abnormality monitoring rule is disassembled to obtain the parameter item to be monitored corresponding to the abnormality monitoring rule, the allowable value range of the parameter item to be monitored, and the alarm operation when the value of the parameter item to be monitored exceeds the allowable value range.
[0138] For example, the abnormality monitoring rule is "When the steamer temperature exceeds 105°C, issue a high temperature warning; when the steamer temperature falls below 95°C, issue a water level check warning." Analyzing the abnormality monitoring rule, it is determined that the parameter to be monitored is the steamer's real-time temperature, and the allowable range of real-time temperature is 95°C to 105°C. The corresponding alarm actions are: Alarm Action a, issue a high temperature warning; Alarm Action b, issue a water level check warning.
[0139] S404: Determine a corresponding collection rule and at least one alarm rule according to at least one parameter item to be monitored, an allowable value range of each parameter item to be monitored, and an alarm operation.
[0140] In this step, after extracting the corresponding parameter items to be monitored, the allowed value range and the alarm operation from each abnormal monitoring rule, the collection rule is determined according to at least one parameter item to be monitored, and the corresponding alarm rule is determined according to the allowed value range and the alarm operation of each parameter item to be monitored.
[0141] For example, the parameter item to be monitored is the real-time temperature of the steamer, the allowable value range of the parameter item to be monitored is 95°C-105°C, and the alarm operations are: alarm operation a, issuing a high temperature prompt; alarm operation b, issuing a water volume check prompt.
[0142] According to the allowable value range and alarm operation, alarm rule a is obtained: when the real-time temperature of the steamer is greater than 105 degrees Celsius, the output is "The temperature is too high, please turn off the steamer immediately and check the equipment"; alarm rule b is: when the real-time temperature of the steamer is less than 95 degrees Celsius, the output is "The temperature is too low, please check the water volume".
[0143] S405: Determine an interception rule that triggers the scene to be monitored, and determine definition information based on the interception rule, the collection rule, and at least one alarm rule.
[0144] In this step, the interception rule is used to determine whether the corresponding monitoring slice is triggered. To ensure real-time and reliable monitoring of the monitoring slice, it is necessary to define the interception rule that triggers the monitoring slice. Based on the interception rule, the previously obtained collection rule, and at least one alarm rule, the corresponding initial monitoring slice is defined to obtain the monitoring slice.
[0145] Specifically, each monitored scene is analyzed to determine the interception rule that triggers the monitored scene. Definition information is then determined based on the interception rule, the corresponding collection rule for the monitored scene, and at least one alarm rule. This definition information is used to define the initial monitoring slice corresponding to the monitored scene.
[0146] S406: Perform a definition operation on the initial monitoring slice according to the definition information to obtain a corresponding monitoring slice.
[0147] In this step, after determining the definition information corresponding to each scene to be monitored, a definition operation is performed on the initial monitoring slice of the scene to be monitored according to each definition information.
[0148] The present application provides a business monitoring method for a smart kitchen appliance system. Based on the functional modules of the system's business layer and the data middle platform, multiple scenarios to be monitored and at least one abnormal monitoring rule for each scenario to be monitored are determined. An initial monitoring slice is created based on at least one abnormal monitoring rule for each scenario to be monitored, and definition information is determined. Afterwards, a monitoring operation is performed on the corresponding initial monitoring slice based on the definition information to obtain a corresponding monitoring slice. In this way, the obtained monitoring slice can effectively monitor the business of the smart kitchen appliance system, while improving the reliability of the smart kitchen appliance system.
[0149] Figure 5 This is a schematic diagram of the structure of a business monitoring device for a smart kitchen appliance system provided in an embodiment of the present application. Applied to BCP perspective monitoring middleware, the BCP perspective monitoring middleware is set in the smart kitchen appliance system and is used to monitor the data transmitted by the data middle platform and business layer of the smart kitchen appliance system. Figure 5 As shown, the business monitoring device 50 of the smart kitchen appliance system includes: an information determination module 501, an abnormality determination module 502 and an abnormality processing module 503, wherein:
[0150] The information determination module 501 is used to determine a triggered target monitoring slice from a plurality of predefined monitoring slices based on the transmission data of the business layer and the data middle platform, wherein each monitoring slice is used to determine whether the corresponding monitored scenario is operating normally;
[0151] The information determination module 501 is further configured to determine the number of target monitoring slices and definition information of each target monitoring slice;
[0152] The abnormality determination module 502 is used to execute the target monitoring slice according to the number of slices and the definition information of each target monitoring slice, and determine whether to trigger an abnormality alarm;
[0153] The exception handling module 503 is used to determine the abnormal monitoring slice if an abnormal alarm is triggered, and perform an alarm operation according to the definition information of the abnormal monitoring slice.
[0154] In a possible implementation, the abnormality determination module 502 is further configured to:
[0155] If the number of slices is 1, the target monitoring slice is executed according to the definition information, and monitoring is performed to determine whether an abnormal alarm is triggered;
[0156] If the number of slices is greater than 1, the priority of each target monitoring slice is determined, and the execution order of each target monitoring slice is determined in descending order of priority;
[0157] According to the execution order and the definition information of each target monitoring slice, the target monitoring slice is executed, and whether an abnormal alarm is triggered is monitored.
[0158] In a possible implementation, the abnormality determination module 502 is further configured to:
[0159] Based on the collection rule, determining at least one parameter item to be monitored and a corresponding value from the transmission data;
[0160] Determining a target alarm rule corresponding to each parameter item to be monitored from at least one alarm rule;
[0161] Whether to trigger an abnormal alarm is determined based on the result of whether the value corresponding to the parameter item to be monitored triggers the corresponding target alarm rule.
[0162] In a possible implementation, the exception handling module 503 is further configured to:
[0163] Determining a triggered alarm rule and a corresponding alarm operation from at least one alarm rule in the definition information;
[0164] Execute the alarm operation and update the alarm count;
[0165] When the updated alarm number is greater than or equal to the alarm number threshold, abnormal prompt information is generated and output based on the record corresponding to each abnormal alarm, wherein the abnormal prompt information is used to prompt the user to verify and adjust the triggered alarm rules, or the execution steps of the corresponding monitored scene.
[0166] In a possible implementation, the information determination module 501 is further configured to:
[0167] Determine the definition information of each monitoring slice and obtain the interception rules of the corresponding monitoring slice from each definition information;
[0168] determining, according to the transmission data, a target interception rule to be triggered from a plurality of interception rules;
[0169] According to the monitoring slice corresponding to the target interception rule, the triggered target monitoring slice is determined.
[0170] In a possible implementation, the information determination module 501 is further configured to:
[0171] Determine, based on the functional modules of the business layer and the data middle platform, multiple scenarios to be monitored and at least one anomaly monitoring rule corresponding to each scenario to be monitored;
[0172] For each scene to be monitored, an initial monitoring slice is created according to at least one abnormality monitoring rule corresponding to the scene to be monitored, and the initial monitoring slice is defined to obtain a corresponding monitoring slice.
[0173] In a possible implementation, the information determination module 501 is further configured to:
[0174] Creating an initial monitoring slice of the scene to be monitored;
[0175] Extracting a parameter item to be monitored, an allowable value range of the parameter item to be monitored, and an alarm operation from each abnormality monitoring rule;
[0176] Determine corresponding collection rules and at least one alarm rule according to at least one parameter item to be monitored, an allowable value range of each parameter item to be monitored, and an alarm operation;
[0177] Determining an interception rule that triggers the scene to be monitored, and determining definition information based on the interception rule, the collection rule, and the at least one alarm rule;
[0178] A definition operation is performed on the initial monitoring slice according to the definition information to obtain a corresponding monitoring slice.
[0179] This embodiment provides a business monitoring device for a smart kitchen appliance system, which can execute the business monitoring method for a smart kitchen appliance system provided by the above method embodiment. Its implementation principle and technical effects are similar, and are not described in detail in this embodiment.
[0180] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 6As shown, the electronic device 60 includes: a processor 601, and a memory 602 in communication with the processor 601. Optionally, the electronic device 60 also includes a communication component 603. The processor 601, the memory 602 and the communication component 603 are connected via a bus 604.
[0181] The memory 602 stores computer-executable instructions;
[0182] The processor 601 executes the computer-executable instructions stored in the memory 602 to implement the business monitoring method of the smart kitchen appliance system as described above.
[0183] The at least one processor 601 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.
[0184] Optionally, in a specific implementation, the processor 601 and the memory 602 are implemented independently. The processor 601 and the memory 602 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, control buses, etc., but this does not mean there is only one bus or only one type of bus.
[0185] Optionally, in a specific implementation, if the processor 601 and the memory 602 are integrated on a chip, the processor 601 and the memory 602 can communicate through an internal interface.
[0186] The present application also provides a computer storage medium, which stores computer execution instructions. When the processor executes the computer execution instructions, the technical solution of the business monitoring method of the aforementioned smart kitchen appliance system is implemented.
[0187] The computer-readable storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The computer-readable storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.
[0188] An exemplary readable storage medium is coupled to a processor, so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application-specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in the control device of the clothing processing device.
[0189] The division of units described above is merely a logical functional division. In actual implementation, other divisions may be employed. For example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not implemented. Furthermore, any coupling or direct coupling or communication connection shown or discussed between units may be an indirect coupling or communication connection via an interface, device, or unit, and may be electrical, mechanical, or other.
[0190] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.
[0191] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
[0192] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.
[0193] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.
[0194] So far, the technical solution of the present application has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the scope of protection of the present application is obviously not limited to these specific embodiments. The above embodiments are only used to illustrate the technical solution of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solution to deviate from the scope of the technical solutions of the embodiments of the present application.
Claims
1. A business monitoring method for a smart kitchen appliance system, characterized in that: Applied to BCP perspective monitoring middleware, the BCP perspective monitoring middleware is set in the smart kitchen appliance system and is used to monitor data transmitted by the data middle platform and business layer of the smart kitchen appliance system. The method includes: Determine a triggered target monitoring slice from a plurality of predefined monitoring slices according to the transmission data of the business layer and the data middle platform, wherein each monitoring slice is used to determine whether the corresponding monitored scenario is operating normally; Determining the number of slices of the target monitoring slice and definition information of each target monitoring slice; Execute the target monitoring slice according to the number of slices and definition information of each target monitoring slice, and determine whether to trigger an abnormality alarm; If an abnormal alarm is triggered, the abnormal monitoring slice is determined, and an alarm operation is performed according to the definition information of the abnormal monitoring slice.
2. The method according to claim 1, characterized in that The step of executing the target monitoring slice according to the number of slices and definition information of each target monitoring slice, and determining whether to trigger an abnormality alarm, includes: If the number of slices is 1, the target monitoring slice is executed according to the definition information, and monitoring is performed to determine whether an abnormal alarm is triggered; If the number of slices is greater than 1, the priority of each target monitoring slice is determined, and the execution order of each target monitoring slice is determined in descending order of priority; According to the execution order and the definition information of each target monitoring slice, the target monitoring slice is executed, and whether an abnormal alarm is triggered is monitored.
3. The method according to claim 2, characterized in that The definition information includes a collection rule and at least one alarm rule, and executing the target monitoring slice according to the definition information and monitoring whether an abnormal alarm is triggered includes: Based on the collection rule, determining at least one parameter item to be monitored and a corresponding value from the transmitted data; Determining a target alarm rule corresponding to each parameter item to be monitored from at least one alarm rule; Whether to trigger an abnormal alarm is determined based on the result of whether the value corresponding to the parameter item to be monitored triggers the corresponding target alarm rule.
4. The method according to claim 3, characterized in that The performing of the alarm operation according to the definition information of the abnormal monitoring slice includes: Determining a triggered alarm rule and a corresponding alarm operation from at least one alarm rule in the definition information; Execute the alarm operation and update the alarm count; When the updated alarm number is greater than or equal to the alarm number threshold, abnormal prompt information is generated and output based on the record corresponding to each abnormal alarm, wherein the abnormal prompt information is used to prompt the user to verify and adjust the triggered alarm rules, or the execution steps of the corresponding monitored scene.
5. The method according to claim 4, characterized in that The definition information further includes an interception rule, and the determination of a triggered target monitoring slice from a plurality of predefined monitoring slices based on the transmission data of the business layer and the data middle platform includes: Determine the definition information of each monitoring slice and obtain the interception rules of the corresponding monitoring slice from each definition information; determining, according to the transmission data, a target interception rule to be triggered from a plurality of interception rules; According to the monitoring slice corresponding to the target interception rule, the triggered target monitoring slice is determined.
6. The method according to claim 1, characterized in that Before determining the triggered target monitoring slice from the predefined multiple monitoring slices, the method further includes: Determine, based on the functional modules of the business layer and the data middle platform, multiple scenarios to be monitored and at least one anomaly monitoring rule corresponding to each scenario to be monitored; For each scene to be monitored, an initial monitoring slice is created according to at least one abnormality monitoring rule corresponding to the scene to be monitored, and the initial monitoring slice is defined to obtain a corresponding monitoring slice.
7. The method according to claim 6, characterized in that The step of creating an initial monitoring slice according to at least one abnormality monitoring rule corresponding to the scene to be monitored, and defining the initial monitoring slice to obtain a corresponding monitoring slice includes: Creating an initial monitoring slice of the scene to be monitored; Extracting a parameter item to be monitored, an allowable value range of the parameter item to be monitored, and an alarm operation from each abnormality monitoring rule; Determine corresponding collection rules and at least one alarm rule according to at least one parameter item to be monitored, an allowable value range of each parameter item to be monitored, and an alarm operation; Determining an interception rule that triggers the scene to be monitored, and determining definition information based on the interception rule, the collection rule, and the at least one alarm rule; A definition operation is performed on the initial monitoring slice according to the definition information to obtain a corresponding monitoring slice.
8. A business monitoring device for a smart kitchen appliance system, characterized in that: Applied to BCP perspective monitoring middleware, the BCP perspective monitoring middleware is set in the smart kitchen appliance system and is used to monitor the data transmitted by the data center and business layer of the smart kitchen appliance system, including: an information determination module, an anomaly determination module and an anomaly handling module, wherein: The information determination module is used to determine a triggered target monitoring slice from a plurality of predefined monitoring slices based on the transmission data of the business layer and the data middle platform, wherein each monitoring slice is used to determine whether the corresponding monitored scenario is operating normally; The information determination module is further used to determine the number of slices of the target monitoring slice and the definition information of each target monitoring slice; The abnormality determination module is used to execute the target monitoring slice according to the number of slices and the definition information of each target monitoring slice, and determine whether to trigger an abnormality alarm; The exception handling module is used to determine the abnormal monitoring slice if an abnormal alarm is triggered, and perform an alarm operation according to the definition information of the abnormal monitoring slice.
9. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the business monitoring method for the smart kitchen appliance system according to any one of claims 1 to 7.