Method and device for controlling intelligent equipment in group control system

Abstract

The invention discloses a control method and device for intelligent equipment in a group control system. The method comprises the steps that after a control instruction is received, a control signal is generated according to the control instruction; the control signal is sent to the target intelligent equipment, so that the target intelligent equipment operates according to the control signal; in the process that the target intelligent equipment operates according to the control signal, when a query event is monitored, responding to the query event to query a multi-dimensional state parameter of the target intelligent equipment; adjusting a control strategy of the target intelligent equipment according to the multi-dimensional state parameters and the equipment operation result information to obtain a target control strategy; and controlling the target intelligent equipment according to the target control strategy. The technical problem that in a group control system in the prior art, due to factors such as equipment performance difference, network delay and instruction transmission errors, part of intelligent equipment may not correctly execute control instructions, and the overall control efficiency and safe operation of the equipment are affected is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent device group control, and in particular to a control method and apparatus for intelligent devices in a group control system. Background Art

[0002] Group control plays a crucial role in modern smart device management and control, allowing users or management systems to remotely operate and control a large number of smart devices simultaneously. However, in practice, due to various factors, such as device performance differences, network latency, and command transmission errors, some devices may fail to correctly execute control commands during group control. This not only affects overall control efficiency but also poses a potential threat to the safe operation of the devices.

[0003] Currently, the above problems are generally addressed by manually checking device status, setting up command retry mechanisms, and troubleshooting through log analysis. However, these methods are either inefficient or unable to accurately determine whether the command was executed successfully in real time.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0005] The embodiments of the present invention provide a method and apparatus for controlling intelligent devices in a group control system, so as to at least solve the technical problem in the related art that, due to factors such as device performance differences, network delays, and instruction transmission errors, some intelligent devices may not be able to correctly execute control instructions in the group control system, thereby affecting the overall control efficiency and safe operation of the equipment.

[0006] According to one aspect of an embodiment of the present invention, a method for controlling an intelligent device in a group control system is provided, comprising: after receiving a control instruction, generating a control signal according to the control instruction, wherein the control instruction includes target device information and device operation result information, the target device information is identification information of the target intelligent device, and the target intelligent device is the device requesting control in the group control system; sending the control signal to the target intelligent device so that the target intelligent device operates according to the control signal; when a query event is monitored during the operation of the target intelligent device according to the control signal, responding to the query event to query multidimensional state parameters of the target intelligent device, wherein the query event is a pre-set event for querying the multidimensional state parameters of the target intelligent device, and the multidimensional state parameters are parameters obtained by querying the state parameters of the target intelligent device from multiple dimensions; adjusting the control strategy of the target intelligent device according to the multidimensional state parameters and the device operation result information to obtain a target control strategy; and controlling the target intelligent device according to the target control strategy.

[0007] Optionally, the control method of the smart device in the group control system further includes: when sending the control signal to the target smart device, recording the sending time of the control signal; and determining the query time of the multi-dimensional state parameter according to the sending time.

[0008] Optionally, during the process of the target smart device operating according to the control signal, a query event is monitored, including at least one of the following: when the query time arrives, it is determined that the query event is monitored; when an abnormality is detected in the target smart device, it is determined that the query event is monitored; when a multi-dimensional status parameter query request is received, it is determined that the query event is monitored.

[0009] Optionally, determining the query time of the multidimensional state parameters based on the sending time includes: obtaining the device type and application scenario of the target smart device; obtaining the complexity of the control instruction; determining the query period of the multidimensional state parameters based on the device type, the application scenario and the complexity; and determining the query time based on the query period and the sending time.

[0010] Optionally, determining the query period of the multidimensional state parameters according to the device type, the application scenario and the complexity includes: determining the query period corresponding to the device type, the application scenario and the complexity by determining a model, wherein the determination model is a model obtained by machine learning training using multiple sets of training data, each of the multiple sets of training data includes: historical device type, historical application scenario, historical complexity and historical query period, the historical device type, the historical application scenario and the historical complexity are inputs of the determination model, and the historical query period is output of the determination model.

[0011] Optionally, the control method of the intelligent device in the group control system further includes: determining the parameter type of the multi-dimensional state parameter and the parameter threshold of the state parameter corresponding to each parameter type according to the device type and the application scenario.

[0012] Optionally, the control strategy of the target smart device is adjusted according to the multidimensional state parameters and the device operation result information to obtain the target control strategy, including: comparing the multidimensional state parameters with the device operation result information to obtain a comparison result; adjusting the control strategy according to the comparison result to obtain the target control strategy.

[0013] Optionally, the control strategy is adjusted according to the comparison result to obtain the target control strategy, including: when the comparison result is that the multi-dimensional state parameters are consistent with the device operation result information, adjusting the control strategy to send a confirmation message, wherein the confirmation message is used to confirm that the control instruction is successfully executed; when the comparison result is that the multi-dimensional state parameters are inconsistent with the device operation result information, adjusting the control strategy to trigger an exception handling mechanism, wherein the exception handling mechanism is a mechanism for handling abnormal execution operations of the target smart device.

[0014] Optionally, the exception handling mechanism includes at least one of the following: resending the control instruction, issuing an alarm signal, recording an error log, and adjusting the control strategy; wherein, adjusting the control strategy includes at least one of the following: adjusting the sending frequency of the control instruction, and optimizing the configuration information of the target smart device.

[0015] Optionally, the control method of the intelligent device in the group control system also includes: determining the anomaly detection result corresponding to the multidimensional state parameter through an anomaly detection model, wherein the anomaly detection model is obtained through machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: historical multidimensional state parameters, historical anomaly detection results corresponding to the historical multidimensional state parameters, the historical multidimensional state is the input of the anomaly detection model, and the historical anomaly detection result is the output of the anomaly detection model.

[0016] According to another aspect of an embodiment of the present invention, a control apparatus for an intelligent device in a group control system is provided, comprising: a generating unit for generating a control signal according to a control instruction after receiving the control instruction, wherein the control instruction includes target device information and device operation result information, the target device information being identification information of a target intelligent device, and the target intelligent device being a device requesting control in the group control system; a sending unit for sending the control signal to the target intelligent device so that the target intelligent device operates in accordance with the control signal; a monitoring unit for, when a query event is monitored during the operation of the target intelligent device in accordance with the control signal, responding to the query event to query multidimensional state parameters of the target intelligent device, wherein the query event is a pre-set event for querying the multidimensional state parameters of the target intelligent device, and the multidimensional state parameters are parameters obtained by querying the state parameters of the target intelligent device from multiple dimensions; an adjusting unit for adjusting a control strategy of the target intelligent device according to the multidimensional state parameters and the device operation result information to obtain a target control strategy; and a control unit for controlling the target intelligent device in accordance with the target control strategy.

[0017] Optionally, the control device of the intelligent device in the group control system also includes: a recording unit, used to record the sending time of the control signal when sending the control signal to the target intelligent device; and a first determination unit, used to determine the query time of the multidimensional state parameter according to the sending time.

[0018] Optionally, in the process of the target smart device running according to the control signal, a query event is monitored, including at least one of the following: a first determination module, used to determine that the query event is monitored when the query time arrives; a second determination module, used to determine that the query event is monitored when an abnormality is detected in the target smart device; a third determination module, used to determine that the query event is monitored when a multi-dimensional status parameter query request is received.

[0019] Optionally, the first determination unit includes: a first acquisition module for acquiring the device type and application scenario of the target smart device; a second acquisition module for acquiring the complexity of the control instruction; a fourth determination module for determining the query period of the multidimensional state parameter based on the device type, the application scenario and the complexity; and a fifth determination module for determining the query time based on the query period and the sending time.

[0020] Optionally, the fourth determination module includes: a first determination submodule, used to determine the query period corresponding to the device type, the application scenario and the complexity through a determination model, wherein the determination model is a model obtained by machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: historical device type, historical application scenario, historical complexity and historical query period, the historical device type, the historical application scenario and the historical complexity are the input of the determination model, and the historical query period is the output of the determination model.

[0021] Optionally, the control device of the intelligent device in the group control system further includes: a second determination submodule, used to determine the parameter type of the multidimensional state parameter and the parameter threshold of the state parameter corresponding to each parameter type according to the device type and the application scenario.

[0022] Optionally, the adjustment unit includes: a comparison module for comparing the multidimensional state parameters with the device operation result information to obtain a comparison result; and an adjustment module for adjusting the control strategy according to the comparison result to obtain the target control strategy.

[0023] Optionally, the adjustment module includes: a first adjustment sub-module, used to adjust the control strategy to send a confirmation message when the comparison result is that the multi-dimensional state parameters are consistent with the device operation result information, wherein the confirmation message is used to confirm that the control instruction is successfully executed; a second adjustment sub-module, used to adjust the control strategy to trigger an exception handling mechanism when the comparison result is that the multi-dimensional state parameters are inconsistent with the device operation result information, wherein the exception handling mechanism is a mechanism for handling abnormal execution operations of the target smart device.

[0024] Optionally, the exception handling mechanism includes at least one of the following: resending the control instruction, issuing an alarm signal, recording an error log, and adjusting the control strategy; wherein, adjusting the control strategy includes at least one of the following: adjusting the sending frequency of the control instruction, and optimizing the configuration information of the target smart device.

[0025] Optionally, the control device of the intelligent device in the group control system also includes: a second determination unit, used to determine the anomaly detection result corresponding to the multidimensional state parameter through an anomaly detection model, wherein the anomaly detection model is obtained through machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: historical multidimensional state parameters, historical anomaly detection results corresponding to the historical multidimensional state parameters, the historical multidimensional state is the input of the anomaly detection model, and the historical anomaly detection result is the output of the anomaly detection model.

[0026] According to another aspect of an embodiment of the present invention, a group control system is further provided, wherein the group control system uses any one of the above-mentioned methods for controlling intelligent devices in a group control system.

[0027] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is further provided, wherein the computer-readable storage medium includes a stored program, wherein the program executes any one of the above-mentioned methods for controlling an intelligent device in a group control system.

[0028] According to another aspect of an embodiment of the present invention, a processor is further provided, which is configured to run a program, wherein the program, when running, executes any one of the above-mentioned methods for controlling an intelligent device in a group control system.

[0029] According to another aspect of an embodiment of the present invention, a computer program product is provided, comprising computer instructions, which, when executed by a processor, execute any one of the above-mentioned methods for controlling an intelligent device in a group control system.

[0030] In an embodiment of the present invention, after receiving a control instruction, a control signal is generated according to the control instruction, wherein the control instruction includes target device information and device operation result information, the target device information is identification information of the target intelligent device, and the target intelligent device is the device requested to be controlled in the group control system; the control signal is sent to the target intelligent device to make the target intelligent device operate according to the control signal; in the process of the target intelligent device operating according to the control signal, when a query event is monitored, the query event is responded to to query the multi-dimensional state parameters of the target intelligent device, wherein the query event is a pre-set event for querying the multi-dimensional state parameters of the target intelligent device, and the multi-dimensional state parameters are parameters obtained by querying the state parameters of the target intelligent device from multiple dimensions; the control strategy of the target intelligent device is adjusted according to the multi-dimensional state parameters and the device operation result information to obtain the target control strategy; and the target intelligent device is controlled according to the target control strategy. Through the technical solution provided by the present invention, it is possible to verify the execution of instructions by real-time monitoring of the multi-dimensional status information of smart devices in combination with preset time points and status thresholds. Once it is found that the status deviates from the expectation, it is immediately determined that the instruction execution has failed, and the purpose of optimizing subsequent operations through an adaptive adjustment mechanism is achieved. This improves the real-time and accuracy of the execution of instructions in the group control system, reduces the need for manual inspection and troubleshooting, and improves the overall control efficiency, thereby solving the technical problem in the related art that in the group control system, due to factors such as device performance differences, network delays, and instruction transmission errors, some smart devices may not be able to correctly execute control instructions, thereby affecting the overall control efficiency and safe operation of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0032] Figure 1 This is a hardware structure block diagram of a mobile terminal for a method for controlling an intelligent device in a group control system according to an embodiment of the present invention;

[0033] Figure 2 is a flow chart of a method for controlling an intelligent device in a group control system according to an embodiment of the present invention;

[0034] Figure 3 is a flow chart of a method for controlling an intelligent device in an optional group control system according to an embodiment of the present invention;

[0035] Figure 4 2 is a schematic diagram of a control device for an intelligent device in a group control system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0036] 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 drawings in 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 should fall within the scope of protection of the present invention.

[0037] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0038] As described in the background, in related art, group control systems can encounter issues such as the inability of some intelligent devices to correctly execute control commands due to factors such as device performance differences, network latency, and command transmission errors, impacting overall control efficiency and device safety. Embodiments of the present invention provide a method and apparatus for controlling intelligent devices in a group control system, a group control system, a computer-readable storage medium, and a processor.

[0039] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0040] The method embodiments provided in the embodiments of the present invention can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a method of controlling an intelligent device in a group control system according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown) a processor 102 (the processor 102 may include but is not limited to a microprocessor MCU or a programmable logic device FPGA and other processing devices) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It will be understood by those skilled in the art that Figure 1The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0041] The memory 104 can be used to store computer programs, such as software programs and modules of application software, such as the computer program corresponding to the control method of the intelligent device in the group control system in the embodiment of the present invention. The processor 102 executes the computer program stored in the memory 104 to execute various functional applications and data processing, thereby implementing the above-mentioned method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. The transmission device 106 is used to receive or transmit data via a network. Specific examples of such networks may include a wireless network provided by the mobile terminal's telecommunications provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0042] Example 1

[0043] According to an embodiment of the present invention, a method embodiment of a method for controlling an intelligent device in a group control system is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0044] Figure 2 Flowchart of a method for controlling an intelligent device in a group control system according to an embodiment of the present invention. Figure 2 As shown, the method includes the following steps:

[0045] Step S202: after receiving the control instruction, generating a control signal according to the control instruction, wherein the control instruction includes target device information and device operation result information, the target device information is the identification information of the target smart device, and the target smart device is the device requesting control in the group control system.

[0046] Optionally, the control instruction may be an instruction input by a user through a main control unit of the group control system, for example, setting the temperature of the room where the air conditioner is located to 26°C.

[0047] Through the above control instructions, users can specify the target smart device in the group control system, that is, the device they want to control or adjust. At the same time, the control instruction can also set the desired operation result, for example, they want the temperature of the room where the air conditioner is located to be 26℃.

[0048] Then, after receiving the control command input by the user, the main control unit of the group control system will generate a corresponding control signal to control the target smart device.

[0049] Optionally, the target device information may include identification information of the target smart device, for example, information that can uniquely identify the target smart device, such as a MAC address and a serial number of the target smart device.

[0050] For example, when the user sets the "whole house cooling" control command through the main control unit, the system will automatically start the air-conditioning equipment in all rooms, and preset the operating temperature threshold to 23℃ to 25℃ and the voltage threshold to 220V±5% to ensure safe operation of the equipment.

[0051] Step S204: sending the control signal to the target smart device so that the target smart device operates according to the control signal.

[0052] In this embodiment, a control signal may be sent to the target smart device, thereby controlling the target smart device to operate according to the control signal, so that the operation of the target smart device meets user needs.

[0053] In addition, the control method of the intelligent device in the group control system provided in the embodiment of the present invention is applied to the group control system, and the group control system here may include: a main control unit, a communication module, a multi-dimensional status monitoring module, an instruction execution confirmation module and an adaptive adjustment module.

[0054] Among them, the main control unit can be responsible for the management and control of the entire group control system, can receive control instructions input by the user, generate corresponding control signals according to the instructions, and coordinate the collaborative work between various modules.

[0055] The above-mentioned communication module is responsible for the communication between the main control unit and the target device, receives the control signal sent by the main control unit, and transmits it to the target smart device. It actively queries the current status of the target device at a preset time point or according to the adaptive adjustment strategy, and feeds back the status information to the main control unit.

[0056] In addition, real-time monitoring and recording are performed based on the monitoring parameters and thresholds preset by the main control unit. Examples of preset monitoring parameters and thresholds are as follows:

[0057] Operating temperature: The threshold range is 40℃-60℃. Temperatures outside this range are considered abnormal.

[0058] Voltage: The threshold range is 220V±10%. Anything outside this range is considered abnormal.

[0059] Current: The threshold range is ±20% of the device's rated current. Any current outside this range is considered abnormal.

[0060] Power consumption: Set a reasonable power consumption threshold based on the device type. Exceeding the threshold is considered an abnormality.

[0061] Network delay: The threshold range is within 50ms. Any delay beyond this range is considered a network anomaly.

[0062] Data throughput: Set a reasonable throughput threshold based on the device type and application scenario. Exceeding or falling below the threshold is considered an abnormality.

[0063] In addition, the main control unit compares the monitoring results with the expected status to determine whether the equipment is operating normally. This will be explained in detail below.

[0064] Step S206, when the target smart device monitors a query event during the operation of the target smart device according to the control signal, respond to the query event to query the multi-dimensional status parameters of the target smart device, wherein the query event is a pre-set event for querying the multi-dimensional status parameters of the target smart device, and the multi-dimensional status parameters are parameters obtained by querying the status parameters of the target smart device from multiple dimensions.

[0065] Optionally, the above-mentioned multi-dimensional state parameters can be obtained by monitoring the parameters obtained by the multi-dimensional state monitoring module to monitor the multi-dimensional state parameters of the target smart device in real time, including but not limited to the device's operating temperature (unit: ° C), voltage (unit: V), current (unit: A), power consumption (unit: W), network latency (unit: ms), data throughput (unit: Mbps), etc. It can be a measurement value or indicator used to comprehensively describe multiple different aspects of a system, device, or process at a specific moment or period. In the fields of smart devices, industrial automation, Internet of Things (IoT) systems, etc., in order to more accurately assess the operating status of the device and ensure its efficient and safe operation, a series of interrelated but independent state parameters are usually monitored. These parameters together constitute a multi-dimensional state parameter set.

[0066] In the embodiment of the present invention, the multi-dimensional state parameters cover various key attributes that may appear during the operation of the device, including but not limited to: 1) physical state parameters: such as temperature, humidity, pressure, vibration, current, voltage, power, position, movement speed, etc., which are basic measurement values reflecting the physical characteristics of the device; 2) health state parameters: monitoring the health status of the device, including the degree of equipment aging, wear status, fault prediction indicators, etc., which are helpful for early warning and maintenance; 3) performance parameters: measuring the performance of the device when performing tasks, such as processing speed, response time, throughput, data transmission rate, energy consumption efficiency, etc. These parameters reflect the performance level and work efficiency of the device; 4) environmental parameters: the condition of the environment in which the device is located, including the surrounding Temperature, humidity, light intensity, electromagnetic interference level, etc., which directly affect the working status and life of the device; 5) Behavioral or activity parameters: status information of the device when performing specific actions or tasks, such as power on / off times, operation frequency, usage time, load conditions, etc., which can help understand the device's usage pattern and workload; 6) Network status parameters: For networked devices, network latency, connection status, packet loss rate, security level, etc. are all important dimensions, which affect the device's communication capabilities and network security; 6) Software status parameters: software version, update status, running process, system load, etc. on the device. These parameters reflect the operating status of the device software level and are crucial to ensuring software compatibility and security.

[0067] By collecting and analyzing these multi-dimensional status parameters in real time, the system can gain a comprehensive view of equipment operation, enabling timely identification of potential issues and preventive maintenance, as well as optimizing equipment configuration and improving overall system efficiency. In intelligent device group control systems, real-time monitoring and analysis of multi-dimensional status parameters is fundamental to ensuring effective command execution and improving system reliability and response speed.

[0068] Here, while the target smart device is operating according to the control signal, it can monitor the query event. Once the query event is monitored, it can respond to the query event, thereby querying the multi-dimensional state parameters of the target smart device.

[0069] Step S208 : adjusting the control strategy of the target smart device according to the multi-dimensional state parameters and the device operation result information to obtain a target control strategy.

[0070] Optionally, the above-mentioned device operation result information may be the operation result of the target smart device under the action of the control signal.

[0071] Here, the control strategy of the target immature device can be adjusted according to the above multi-dimensional state parameters and device operation result information, so as to obtain the target control strategy.

[0072] Step S210: Control the target smart device according to the target control strategy.

[0073] As can be seen from the above, after receiving a control instruction, a control signal is generated according to the control instruction, wherein the control instruction includes target device information and device operation result information, the target device information is the identification information of the target smart device, and the target smart device is the device requesting control in the group control system; the control signal is sent to the target smart device so that the target smart device operates in accordance with the control signal; when the target smart device monitors a query event during the operation of the control signal, the query event is responded to to query the multi-dimensional state parameters of the target smart device, wherein the query event is a pre-set event for querying the multi-dimensional state parameters of the target smart device, and the multi-dimensional state parameters are parameters obtained by querying the state parameters of the target smart device from multiple dimensions; the control strategy of the target smart device is adjusted according to the multi-dimensional state parameters and the device operation result information to obtain a target control strategy; the target smart device is controlled according to the target control strategy, thereby realizing the verification of the instruction execution status by real-time monitoring of the multi-dimensional state information of the smart device in combination with the preset time point and state threshold. Once the state deviates from the expectation, the instruction execution is immediately determined to have failed, and the subsequent operation is optimized through the adaptive adjustment mechanism, thereby improving the real-time and accuracy of the instruction execution of the group control system, reducing the need for manual inspection and troubleshooting, and improving the overall control efficiency.

[0074] Therefore, the above-mentioned technical solution provided by the embodiment of the present invention solves the technical problem in the related technology that in the group control system, due to factors such as device performance differences, network delays, and instruction transmission errors, some smart devices may not be able to correctly execute control instructions, thereby affecting the overall control efficiency and safe operation of the equipment.

[0075] According to the above embodiment of the present invention, the control method of the smart device in the group control system further includes: when sending the control signal to the target smart device, recording the sending time of the control signal; and determining the query time of the multi-dimensional state parameter according to the sending time.

[0076] In this embodiment, the master control unit in the group control system generates a corresponding control signal and transmits it to the target smart device via the communication module. When the control signal is transmitted to the target smart device via the communication module, the transmission time of the control signal is recorded and, based on the transmission time, one or more subsequent time points are preset for querying the device status.

[0077] In the embodiment of the present invention, the preset time point (i.e., query event) can be set according to the device type, application scenario, and complexity of the control instruction, such as querying the device status every 5 packets. This will be explained in detail below and will not be repeated here.

[0078] When a control signal is sent, the system records the time it was sent and determines the query time for multi-dimensional status parameters based on the device type, application scenario, and complexity of the control command. This step ensures that status parameter queries are linked to the time of command execution, improving the timeliness and accuracy of status monitoring.

[0079] According to the above embodiment of the present invention, in the process of the target smart device operating according to the control signal, a query event is monitored, including at least one of the following: when the query time arrives, it is determined that the query event is monitored; when an abnormality is detected in the target smart device, it is determined that the query event is monitored; when a multi-dimensional status parameter query request is received, it is determined that the query event is monitored.

[0080] In this embodiment, query events can be monitored in a variety of ways. For example, the query time determined above can be monitored. If the query time arrives, it is determined that the query time has been monitored. When an abnormality is detected in the target smart device, it can be determined that the query time has been monitored. When a multi-dimensional status parameter query request from the user is received, it can be determined that the query time has been monitored.

[0081] The query event triggering mechanism here ensures that the query of status parameters can not only follow the preset rules, but also flexibly respond to abnormal conditions, thereby improving the response speed and reliability of the system.

[0082] According to the above embodiment of the present invention, the query time of the multidimensional state parameters is determined according to the sending time, including: obtaining the device type and application scenario of the target smart device; obtaining the complexity of the control instruction; determining the query period of the multidimensional state parameters according to the device type, application scenario and complexity; determining the query time according to the query period and the sending time.

[0083] Optionally, the complexity of the above control instruction refers to the number of processing steps required to execute the instruction, the depth of data interaction, and the degree of requirement for system resources. The complexity of control instructions can be determined from the following aspects: the number of steps (the more logical steps an instruction needs to go through to execute, the higher its complexity. For example, a simple switch instruction only needs to change the power state of the device, while a complex scheduling instruction may involve multiple steps such as continuous monitoring of the device status, data analysis, feedback loops, etc.), data interaction (the amount of data involved in the execution of the instruction, the data type, and the complexity of data processing. Instructions with large amounts of data or instructions that require complex data processing (such as image recognition and speech analysis) have higher complexity), resource requirements (computing resources (CPU, GPU), storage resources (RAM, hard disk space), and network resources (bandwidth, latency) required for instruction execution. Resource-intensive instructions are more complex because they may require more system support to complete successfully), dependencies (whether the execution of the instruction depends on the status or response of other devices or systems. If the completion of the instruction requires waiting for the response of other devices or close collaboration with other systems, then its complexity will increase accordingly), fault tolerance (the sensitivity of the instruction to errors and the ability to handle fault tolerance. Some instructions may be very sensitive to errors and require additional error detection and correction mechanisms, which also increases the complexity of the instruction), etc.

[0084] In this embodiment, the query period of the multi-dimensional state parameters can be determined based on the above-mentioned device type, application scenario, and complexity. In a group control system, different types of smart devices (such as air conditioners, refrigerators, lighting systems), different application scenarios (such as home, office, industrial production environment), and the complexity of control instructions (such as simple switch commands or complex scheduling programs) will affect the most suitable query period for the multi-dimensional state parameters. A query period that is too short may cause excessive system load and increase energy consumption, while a query period that is too long may miss the immediate change of the device status, affecting the timeliness and accuracy of fault detection. Therefore, the query time can be determined here based on the above-mentioned query period and sending time.

[0085] According to the above embodiment of the present invention, the query period of the multi-dimensional state parameters is determined according to the device type, application scenario and complexity, including: determining the query period corresponding to the device type, application scenario and complexity by determining the model, wherein the determination model is a model obtained by machine learning training using multiple sets of training data, each set of the multiple sets of training data includes: historical device type, historical application scenario, historical complexity and historical query period, the historical device type, historical application scenario and historical complexity are the input of the determination model, and the historical query period is the output of the determination model.

[0086] In this embodiment, a machine learning model is used to predict the optimal multi-dimensional state parameter query cycle based on characteristic variables such as device type, application scenario, and control instruction complexity. Model training is based on a historical dataset, where each sample contains the device type, application scenario, instruction complexity, and the corresponding actual query cycle performance (such as fault detection speed and system energy consumption). Through regression analysis or other appropriate supervised learning techniques, the model can learn the optimal query frequency under different conditions, thereby enabling dynamic and intelligent query cycle adjustment in actual group control operations.

[0087] According to the above embodiment of the present invention, the control method of the intelligent device in the group control system further includes: determining the parameter type of the multidimensional state parameter and the parameter threshold of the state parameter corresponding to each parameter type according to the device type and application scenario.

[0088] In this embodiment, the system pre-sets the parameter types and thresholds for multi-dimensional status parameters for different equipment types and application scenarios, such as setting the operating temperature threshold to 45°C-55°C and the voltage threshold to 220V±10%. This ensures that status monitoring can be tailored to the characteristics of specific equipment, improving the pertinence and effectiveness of monitoring.

[0089] According to the above embodiment of the present invention, the control strategy of the target intelligent device is adjusted according to the multi-dimensional state parameters and the device operation result information to obtain the target control strategy, including: comparing the multi-dimensional state parameters with the device operation result information to obtain the comparison result; adjusting the control strategy according to the comparison result to obtain the target control strategy.

[0090] In this embodiment, the multi-dimensional state monitoring module receives the multi-dimensional state parameters and compares them with the device state expected based on the control instruction (i.e., the device operation result information). The instruction execution confirmation module determines whether the instruction was successfully executed based on the comparison result and adjusts the control strategy accordingly.

[0091] According to the above embodiment of the present invention, the control strategy is adjusted according to the comparison result to obtain the target control strategy, including: when the comparison result is that the multi-dimensional state parameters are consistent with the device operation result information, the control strategy is adjusted to send a confirmation message, wherein the confirmation message is used to confirm that the control instruction is successfully executed; when the comparison result is that the multi-dimensional state parameters are inconsistent with the device operation result information, the control strategy is adjusted to trigger an exception handling mechanism, wherein the exception handling mechanism is a mechanism for handling abnormal execution operations of the target smart device.

[0092] In this embodiment, if the comparison result shows that the actual state is consistent with the expected state, the instruction execution is confirmed to be successful and a confirmation message is sent to the user; if the actual state is inconsistent with the expected state, the exception handling mechanism is triggered.

[0093] At the same time, anomaly detection algorithms are used to conduct in-depth analysis of status information to identify potential anomalies or failures. Anomaly detection algorithms can be trained based on historical data of device status and can identify abnormal changes in device status.

[0094] According to the above embodiment of the present invention, the exception handling mechanism includes at least one of the following: resending control instructions, issuing alarm signals, recording error logs, and adjusting control strategies; wherein, adjusting the control strategy includes at least one of the following: adjusting the sending frequency of control instructions, and optimizing the configuration information of the target smart device.

[0095] In this embodiment, the exception handling mechanism is specifically implemented as follows: Resending the command: After confirming that the command was not successfully executed, the control command is attempted to be resent, with a maximum retry limit. Issuing an alert: An alert is issued to the user via system logs, email, or SMS messages, indicating an abnormal device status. Recording an error log: Information such as the abnormal status, command execution results, and error time is recorded in the error log for subsequent analysis and processing.

[0096] According to the above embodiment of the present invention, the control method of the intelligent device in the group control system also includes: determining the anomaly detection result corresponding to the multidimensional state parameter through an anomaly detection model, wherein the anomaly detection model is obtained through machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: historical multidimensional state parameters, historical anomaly detection results corresponding to the historical multidimensional state parameters, the historical multidimensional state is the input of the anomaly detection model, and the historical anomaly detection result is the output of the anomaly detection model.

[0097] In this embodiment, through the anomaly detection model, the system can identify abnormal situations in multi-dimensional state parameters, further enhancing the ability to intelligently judge the state of the device.

[0098] Through this approach, the system compares the collected multidimensional status parameters with the expected operational outcomes and adjusts the control strategy of the target intelligent device based on the comparison results. When the device status is consistent with expectations, the system sends a confirmation message, indicating that the instruction was successfully executed. If the status is abnormal, the system triggers the exception handling mechanism and takes a series of measures, such as reissuing instructions, issuing alarms, recording error logs, or adjusting the control strategy, including but not limited to adjusting the instruction frequency and optimizing device configuration, to ensure that the device can operate as expected. In addition, through the anomaly detection model, the system can identify anomalies in the multidimensional status parameters, further enhancing its intelligent judgment of device status.

[0099] Figure 3 FIG. 1 is a flow chart of a control method for an intelligent device in an optional group control system according to an embodiment of the present invention. Figure 3As shown, the user enters control commands through the main control unit to specify the smart device to be controlled. The user can then set multi-dimensional status monitoring information. Upon receiving the command, the main control unit generates a corresponding control signal and transmits it to the target device via the communication module. Simultaneously, the transmission time is recorded, and one or more subsequent time points are preset for device status queries. At the preset time points or based on an adaptive adjustment strategy, the communication module proactively queries the target device's multi-dimensional status parameters and feeds this information back to the main control unit. This status information includes the device's operating temperature, voltage, current, power consumption, network latency, and data throughput.

[0100] Next, after receiving the status information, the multidimensional status monitoring module compares it with the expected device status based on the control instructions. Simultaneously, it invokes an anomaly detection algorithm to conduct in-depth analysis of the status information to identify potential anomalies or faults. This anomaly detection algorithm can be trained using historical device status data and can identify abnormal changes in device status. The instruction execution confirmation module determines whether the instruction has been successfully executed based on the comparison results and the anomaly detection results. If the actual status is consistent with the expected status, the instruction is confirmed to have been successfully executed, and a confirmation message is sent to the user. If the actual status is inconsistent with the expected status, an exception handling mechanism is triggered, such as reissuing the instruction, issuing an alarm, recording an error log, or invoking the adaptive adjustment module. The specific execution method of the exception handling mechanism is set based on the device status and the execution results of the control instruction.

[0101] Furthermore, the adaptive adjustment module dynamically adjusts the control strategies and parameters of the group control system based on the results of the command execution confirmation module and the real-time status of the device. These adjustments include the frequency of control command transmission (dynamically adjusting the frequency of command transmission based on device status and the results of control command execution to improve system response speed and stability), device configuration optimization (adjusting the device's operating mode, power consumption, and other configurations based on device status monitoring results to improve device performance and energy efficiency), and state monitoring parameter and threshold adjustment (dynamically adjusting state monitoring parameters and thresholds based on changes in device status and the results of control command execution to adapt to different scenarios). Through continuous learning and optimization, the performance and stability of the group control system are improved.

[0102] It should be noted that, in an embodiment of the present invention, the adaptive adjustment module is started in the following situations: 1). Instruction execution fails or is abnormal: when the instruction execution confirmation module detects that the actual state is inconsistent with the expected state (such as the device temperature exceeds the threshold, the voltage fluctuation exceeds the allowable range, etc.), adjustment is triggered; 2). Device state is abnormal: for example, network delay exceeds 50ms, data throughput is lower than the set threshold, current or power consumption is abnormal, etc.

[0103] In addition, the decision-making basis for the adjustment action includes: 1) Based on the result of the instruction execution: If the instruction execution fails (such as multiple retries are still invalid), the instruction sending frequency may be reduced or the retry strategy may be adjusted; if the execution is successful but the status parameter is close to the threshold (such as the temperature is close to 60°C), the device configuration may be optimized (such as reducing power consumption) or the monitoring threshold may be adjusted. 2) Based on the real-time device status: If the network delay is high, prioritize reducing the instruction sending frequency to avoid congestion; if the device voltage fluctuates greatly, dynamically adjust the voltage monitoring threshold or switch the device to stable mode; if the data throughput is abnormal, reallocate the device tasks or adjust the throughput monitoring threshold. For example, when the device temperature continues to exceed 60°C, the adaptive module may reduce the control instruction sending frequency, adjust the device working mode (such as switching to low power mode), and update the temperature threshold to 55°C as a warning value.

[0104] Through the above-mentioned technical solution provided by the embodiment of the present invention, the result of instruction execution is judged by comparing the actual state of the device at a specific time point with the expected state, and multi-dimensional state monitoring parameters, anomaly detection algorithms and adaptive adjustment strategies are introduced to improve the reliability, accuracy and adaptability of the group control system. It has the advantages of real-time, accuracy, flexibility and scalability, and can effectively solve the problem of failure of some devices during the group control process, and improve the overall performance and user experience of the group control system. Moreover, it can realize real-time monitoring of the status of intelligent devices, quickly respond to changes in device status, and improve the operating efficiency of the group control system and the control accuracy of intelligent devices. In addition, through the adaptive adjustment mechanism and the exception handling mechanism, the system can intelligently respond to various emergencies, reduce the need for manual intervention, and improve the automation level of the system and user experience. It has the following beneficial effects: 1). It improves the real-time and accuracy of the group control system's command execution, reduces the need for manual inspection and troubleshooting, and improves overall control efficiency; 2). By introducing an adaptive adjustment mechanism, it improves the system's adaptability to differences in device performance and changes in the network environment, enhancing the reliability of the group control system and user experience; 3). The introduction of anomaly detection algorithms can more accurately identify device status anomalies, avoid false alarms and missed alarms, and improve the accuracy of system anomaly handling.

[0105] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0106] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0107] Example 2

[0108] According to an embodiment of the present invention, there is also provided a control device for an intelligent device in a group control system for implementing the control method for an intelligent device in the group control system. Figure 4 Schematic diagram of a control device for an intelligent device in a group control system according to an embodiment of the present invention. Figure 4 As shown, the control device of the intelligent device in the group control system includes: a generating unit 401, a sending unit 403, a monitoring unit 405, an adjusting unit 407 and a control unit 409. The device is described below.

[0109] The generation unit 401 is used to generate a control signal according to the control instruction after receiving the control instruction, wherein the control instruction includes target device information and device operation result information. The target device information is the identification information of the target smart device, and the target smart device is the device requesting control in the group control system.

[0110] The sending unit 403 is configured to send the control signal to the target smart device, so that the target smart device operates according to the control signal.

[0111] The monitoring unit 405 is used to respond to a query event to query the multi-dimensional status parameters of the target smart device when a query event is detected during the operation of the target smart device according to the control signal, wherein the query event is a pre-set event for querying the multi-dimensional status parameters of the target smart device, and the multi-dimensional status parameters are parameters obtained by querying the status parameters of the target smart device from multiple dimensions.

[0112] The adjustment unit 407 is configured to adjust the control strategy of the target intelligent device according to the multi-dimensional state parameters and the device operation result information to obtain a target control strategy.

[0113] The control unit 409 is configured to control the target smart device according to the target control strategy.

[0114] It should be noted here that the above-mentioned generation unit 401, sending unit 403, monitoring unit 405, adjustment unit 407 and control unit 409 correspond to steps S202 to S210 in the above-mentioned embodiment. The five units and the corresponding steps implement the same instances and application scenarios, but are not limited to the contents disclosed in the above-mentioned embodiment.

[0115] As can be seen from the above, in the scheme recorded in the above embodiment of the present invention, a generating unit can be used to generate a control signal according to the control instruction after receiving the control instruction, wherein the control instruction includes target device information and device operation result information, the target device information is the identification information of the target intelligent device, and the target intelligent device is the device requesting control in the group control system; the sending unit is used to send the control signal to the target intelligent device so that the target intelligent device operates according to the control signal; the monitoring unit is used to monitor the query event during the process of the target intelligent device operating according to the control signal, and respond to the query event to query the multi-dimensional state parameters of the target intelligent device, wherein the query event is a pre-set multi-dimensional state parameter for querying the target intelligent device. The multi-dimensional state parameters are parameters obtained by querying the state parameters of the target intelligent device from multiple dimensions; then the adjustment unit is used to adjust the control strategy of the target intelligent device according to the multi-dimensional state parameters and the device operation result information to obtain the target control strategy; and the control unit is used to control the target intelligent device according to the target control strategy, thereby realizing the verification of the instruction execution status by real-time monitoring of the multi-dimensional state information of the intelligent device combined with the preset time point and state threshold. Once it is found that the state deviates from the expectation, it is immediately judged that the instruction execution has failed, and the purpose of optimizing subsequent operations through the adaptive adjustment mechanism is to improve the real-time and accuracy of the instruction execution of the group control system, reduce the need for manual inspection and troubleshooting, and improve the overall control efficiency.

[0116] Therefore, the above-mentioned technical solution provided by the embodiment of the present invention solves the technical problem in the related technology that in the group control system, due to factors such as device performance differences, network delays, and instruction transmission errors, some smart devices may not be able to correctly execute control instructions, thereby affecting the overall control efficiency and safe operation of the equipment.

[0117] Optionally, the control device of the smart device in the group control system also includes: a recording unit, used to record the sending time of the control signal when sending the control signal to the target smart device; a first determination unit, used to determine the query time of the multidimensional state parameter according to the sending time.

[0118] Optionally, in the process of the target smart device running according to the control signal, a query event is monitored, including at least one of the following: a first determination module, used to determine that a query event is monitored when the query time arrives; a second determination module, used to determine that a query event is monitored when an abnormality is detected in the target smart device; a third determination module, used to determine that a query event is monitored when a multi-dimensional status parameter query request is received.

[0119] Optionally, the first determination unit includes: a first acquisition module for acquiring the device type and application scenario of the target smart device; a second acquisition module for acquiring the complexity of the control instruction; a fourth determination module for determining the query period of the multidimensional state parameters based on the device type, application scenario and complexity; and a fifth determination module for determining the query time based on the query period and the sending time.

[0120] Optionally, the fourth determination module includes: a first determination submodule, used to determine the query cycle corresponding to the device type, application scenario and complexity through a determination model, wherein the determination model is a model obtained through machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: historical device type, historical application scenario, historical complexity and historical query cycle, the historical device type, historical application scenario and historical complexity are the input of the determination model, and the historical query cycle is the output of the determination model.

[0121] Optionally, the control device of the intelligent device in the group control system further includes: a second determination submodule, configured to determine the parameter type of the multidimensional state parameter and the parameter threshold of the state parameter corresponding to each parameter type according to the device type and the application scenario.

[0122] Optionally, the adjustment unit includes: a comparison module for comparing the multi-dimensional state parameters with the equipment operation result information to obtain a comparison result; and an adjustment module for adjusting the control strategy according to the comparison result to obtain a target control strategy.

[0123] Optionally, the adjustment module includes: a first adjustment sub-module, used to adjust the control strategy to send a confirmation message when the comparison result is that the multi-dimensional state parameters are consistent with the device operation result information, wherein the confirmation message is used to confirm that the control instruction is successfully executed; a second adjustment sub-module, used to adjust the control strategy to trigger an exception handling mechanism when the comparison result is that the multi-dimensional state parameters are inconsistent with the device operation result information, wherein the exception handling mechanism is a mechanism for handling abnormal execution operations of the target smart device.

[0124] Optionally, the exception handling mechanism includes at least one of the following: resending control instructions, issuing alarm signals, recording error logs, and adjusting control strategies; wherein, adjusting control strategies includes at least one of the following: adjusting the sending frequency of control instructions, and optimizing the configuration information of the target smart device.

[0125] Optionally, the control device of the intelligent device in the group control system also includes: a second determination unit, used to determine the anomaly detection result corresponding to the multidimensional state parameter through an anomaly detection model, wherein the anomaly detection model is obtained through machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: historical multidimensional state parameters, historical anomaly detection results corresponding to the historical multidimensional state parameters, the historical multidimensional state is the input of the anomaly detection model, and the historical anomaly detection result is the output of the anomaly detection model.

[0126] According to another aspect of an embodiment of the present invention, a group control system is further provided, which uses any of the above methods for controlling intelligent devices in a group control system.

[0127] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored program, wherein the program executes any one of the above-mentioned methods for controlling an intelligent device in a group control system.

[0128] Optionally, in this embodiment, the computer-readable storage medium may be located in any one of the computer terminals in a computer terminal group in a computer network, or in any one of the communication devices in a communication device group.

[0129] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: after receiving a control instruction, generating a control signal according to the control instruction, wherein the control instruction includes target device information and device operation result information, the target device information is the identification information of the target smart device, and the target smart device is the device requested to be controlled in the group control system; sending the control signal to the target smart device so that the target smart device operates according to the control signal; in the process of the target smart device operating according to the control signal, when a query event is monitored, responding to the query event to query the multi-dimensional state parameters of the target smart device, wherein the query event is a pre-set event for querying the multi-dimensional state parameters of the target smart device, and the multi-dimensional state parameters are parameters obtained by querying the state parameters of the target smart device from multiple dimensions; adjusting the control strategy of the target smart device according to the multi-dimensional state parameters and the device operation result information to obtain the target control strategy; and controlling the target smart device according to the target control strategy.

[0130] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: when sending a control signal to a target smart device, recording the sending time of the control signal; and determining the query time of the multidimensional state parameter according to the sending time.

[0131] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: when the query time arrives, determining that a query event is monitored; when an abnormality is detected in the target smart device, determining that a query event is monitored; when a multi-dimensional status parameter query request is received, determining that a query event is monitored.

[0132] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: obtaining the device type and application scenario of the target smart device; obtaining the complexity of the control instruction; determining the query period of the multidimensional state parameters based on the device type, application scenario and complexity; and determining the query time based on the query period and the sending time.

[0133] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: determining a query cycle corresponding to the device type, application scenario, and complexity by determining a model, wherein the determination model is a model obtained by machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: historical device type, historical application scenario, historical complexity, and historical query cycle, the historical device type, historical application scenario, and historical complexity are inputs to the determination model, and the historical query cycle is the output of the determination model.

[0134] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: determining parameter types of multidimensional state parameters and parameter thresholds of state parameters corresponding to each parameter type according to device type and application scenario.

[0135] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: comparing the multidimensional state parameters with the equipment operation result information to obtain a comparison result; adjusting the control strategy according to the comparison result to obtain a target control strategy.

[0136] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: when the comparison result is that the multi-dimensional state parameters are consistent with the device operation result information, the control strategy is adjusted to send a confirmation message, wherein the confirmation message is used to confirm that the control instruction is successfully executed; when the comparison result is that the multi-dimensional state parameters are inconsistent with the device operation result information, the control strategy is adjusted to trigger an exception handling mechanism, wherein the exception handling mechanism is a mechanism for handling abnormal execution operations of the target smart device.

[0137] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: resending control instructions, issuing alarm signals, recording error logs, and adjusting control strategies; wherein adjusting the control strategy includes at least one of the following: adjusting the sending frequency of control instructions, and optimizing the configuration information of the target smart device.

[0138] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: determining an anomaly detection result corresponding to the multidimensional state parameter through an anomaly detection model, wherein the anomaly detection model is obtained through machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: historical multidimensional state parameters, historical anomaly detection results corresponding to the historical multidimensional state parameters, the historical multidimensional state is the input of the anomaly detection model, and the historical anomaly detection result is the output of the anomaly detection model.

[0139] According to another aspect of an embodiment of the present invention, a processor is further provided, which is used to run a program, wherein when the program is run, any one of the above-mentioned methods for controlling an intelligent device in a group control system is executed.

[0140] According to another aspect of an embodiment of the present invention, a computer program product is provided, including computer instructions. When the computer instructions are executed by a processor, any one of the above-mentioned methods for controlling an intelligent device in a group control system is executed.

[0141] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0142] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0143] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0144] 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 units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0145] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0146] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0147] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A control method for intelligent devices in a group control system, characterized in that: include: After receiving a control instruction, generating a control signal according to the control instruction, wherein the control instruction includes target device information and device operation result information, the target device information is identification information of the target smart device, and the target smart device is the device requesting control in the group control system; sending the control signal to the target smart device so that the target smart device operates according to the control signal; When a query event is detected during operation of the target smart device according to the control signal, the target smart device responds to the query event to query the multi-dimensional state parameters of the target smart device, wherein the query event is a pre-set event for querying the multi-dimensional state parameters of the target smart device, and the multi-dimensional state parameters are parameters obtained by querying the state parameters of the target smart device from multiple dimensions; Adjusting the control strategy of the target smart device according to the multi-dimensional state parameters and the device operation result information to obtain a target control strategy; The target smart device is controlled according to the target control strategy.

2. The control method of intelligent devices in a group control system according to claim 1, characterized in that: Also includes: When sending the control signal to the target smart device, recording the sending time of the control signal; A query time for the multi-dimensional state parameter is determined according to the sending time.

3. The control method of intelligent devices in a group control system according to claim 2, characterized in that: During the process of the target smart device operating according to the control signal, monitoring a query event includes at least one of the following: When the query time arrives, determining that the query event is monitored; When an abnormality is detected in the target smart device, determining that the query event is monitored; When the multi-dimensional state parameter query request is received, it is determined that the query event is monitored.

4. The control method of intelligent devices in a group control system according to claim 2, characterized in that: Determining a query time of the multi-dimensional state parameter according to the sending time includes: Obtain the device type and application scenario of the target smart device; Obtaining the complexity of the control instruction; Determining a query period for the multidimensional state parameter according to the device type, the application scenario, and the complexity; The query time is determined according to the query period and the sending time.

5. The control method of intelligent devices in a group control system according to claim 4, characterized in that: Determining a query period for the multi-dimensional state parameter according to the device type, the application scenario, and the complexity includes: By determining a model, the query cycle corresponding to the device type, the application scenario and the complexity is determined, wherein the determination model is a model obtained by machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: historical device type, historical application scenario, historical complexity and historical query cycle, the historical device type, the historical application scenario and the historical complexity are the input of the determination model, and the historical query cycle is the output of the determination model.

6. The method for controlling intelligent devices in a group control system according to claim 4, characterized in that: Also includes: The parameter types of the multi-dimensional state parameters and the parameter thresholds of the state parameters corresponding to the parameter types are determined according to the device type and the application scenario.

7. The control method of intelligent devices in a group control system according to claim 1, characterized in that: Adjusting the control strategy of the target smart device according to the multi-dimensional state parameter and the device operation result information to obtain a target control strategy includes: Comparing the multi-dimensional state parameter with the device operation result information to obtain a comparison result; The control strategy is adjusted according to the comparison result to obtain the target control strategy.

8. The method for controlling intelligent devices in a group control system according to claim 7, characterized in that: Adjusting the control strategy according to the comparison result to obtain the target control strategy includes: When the comparison result shows that the multi-dimensional state parameter is consistent with the device operation result information, adjusting the control strategy to send a confirmation message, wherein the confirmation message is used to confirm that the control instruction is successfully executed; When the comparison result is that the multi-dimensional state parameter is inconsistent with the device operation result information, the control strategy is adjusted to trigger an exception handling mechanism, wherein the exception handling mechanism is a mechanism for handling abnormal execution operations of the target smart device.

9. The method for controlling intelligent devices in a group control system according to claim 8, characterized in that: The exception handling mechanism includes at least one of the following: resending the control instruction, issuing an alarm signal, recording an error log, and adjusting the control strategy; wherein, adjusting the control strategy includes at least one of the following: adjusting the sending frequency of the control instruction and optimizing the configuration information of the target smart device.

10. The method for controlling intelligent devices in a group control system according to claim 1, characterized in that: Also includes: An anomaly detection result corresponding to the multidimensional state parameter is determined by an anomaly detection model, wherein the anomaly detection model is obtained by machine learning training using multiple sets of training data, each of the multiple sets of training data includes: historical multidimensional state parameters, historical anomaly detection results corresponding to the historical multidimensional state parameters, the historical multidimensional state is the input of the anomaly detection model, and the historical anomaly detection results are the output of the anomaly detection model.

11. A control device for intelligent devices in a group control system, characterized in that: include: a generating unit configured to generate a control signal according to a control instruction after receiving the control instruction, wherein the control instruction includes target device information and device operation result information, the target device information is identification information of a target smart device, and the target smart device is a device requesting control in the group control system; a sending unit, configured to send the control signal to the target smart device, so that the target smart device operates according to the control signal; a monitoring unit, configured to, when a query event is monitored during the operation of the target smart device in accordance with the control signal, respond to the query event to query the multi-dimensional state parameters of the target smart device, wherein the query event is a pre-set event for querying the multi-dimensional state parameters of the target smart device, and the multi-dimensional state parameters are parameters obtained by querying the state parameters of the target smart device from multiple dimensions; an adjusting unit, configured to adjust a control strategy of the target smart device according to the multi-dimensional state parameter and the device operation result information to obtain a target control strategy; A control unit is used to control the target intelligent device according to the target control strategy.

12. A group control system, characterized in that: The group control system uses the control method for intelligent devices in the group control system according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored program, wherein the program executes the method for controlling an intelligent device in a group control system according to any one of claims 1 to 10.

14. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the method for controlling an intelligent device in a group control system according to any one of claims 1 to 10.

15. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by the processor, the control method of the intelligent device in the group control system according to any one of claims 1 to 10 is executed.

Images