Equipment management method and system, computer equipment, storage medium and product

Abstract

The invention discloses an equipment management method and system, computer equipment, a storage medium and a product, and relates to the technical field of the Internet of Things, and the disclosed equipment management method comprises the steps: obtaining environment data collected by each piece of to-be-managed equipment, and monitoring each piece of environment data; when it is monitored that changed environment data exists in the environment data, the environment data at the current moment is input into a preset intelligent agent, a management decision output by the intelligent agent is obtained, and the intelligent agent is built based on a large language model in advance; and determining a target device according to the management decision, and controlling the target device based on the management decision. The technical scheme of the invention aims to solve the technical problem of how to reduce the management cost of the equipment.

Description

Technical Field

[0001] The present application relates to the technical field of Internet of Things, and in particular to a device management method, system, computer device, storage medium and product. Background Art

[0002] With the development of intelligent technology, devices in most scenarios can be managed intelligently. However, traditional intelligent management technology is limited by rules, that is, each scenario is designed in advance, and then a set of rules is designed for each scenario. After accurately identifying the scenario, the device can be managed using the rules corresponding to the scenario. It can be seen that when managing devices through traditional intelligent management technology, it takes a lot of time to set up multiple scenarios and the corresponding rules for multiple scenarios, which makes the management cost of the device relatively high.

[0003] Therefore, how to reduce the management cost of equipment is a technical problem that needs to be solved by those skilled in the art. Summary of the invention

[0004] The main purpose of this application is to provide a device management method, system, computer device, storage medium and product, aiming to solve the technical problem of how to reduce the management cost of the device.

[0005] To achieve the above objectives, the present application proposes a device management method, the method comprising:

[0006] Acquire environmental data collected by each device to be managed, and monitor each of the environmental data;

[0007] When it is detected that there is changed environmental data in each of the environmental data, the environmental data at the current moment is input into a preset intelligent agent to obtain a management decision output by the intelligent agent, wherein the intelligent agent is pre-built based on a large language model;

[0008] A target device is determined according to the management decision, and the target device is controlled based on the management decision.

[0009] In one embodiment, the step of controlling the target device based on the management decision includes:

[0010] Obtaining a preset interface corresponding to the target device, and constructing a control instruction according to the management decision;

[0011] The control instruction is transmitted to the target device through the interface, so that the target device adjusts parameters based on the control instruction.

[0012] In one embodiment, before the step of inputting the current environmental data into a preset intelligent agent to obtain the management decision output by the intelligent agent, the method further includes:

[0013] Training a preset intelligent agent through prior data to obtain a trained intelligent agent, wherein the prior data is an instruction input by a user;

[0014] or,

[0015] The preset groups of actual environmental data are used as model input data, and the real management decisions corresponding to each group of actual environmental data are used as model training labels. The preset intelligent agent is trained to obtain a trained intelligent agent.

[0016] In one embodiment, the step of monitoring each of the environmental data includes:

[0017] Divide the environmental data belonging to the same device to be managed into a group, and obtain the environmental data sets corresponding to each of the devices to be managed;

[0018] Based on the collection time corresponding to each of the environmental data, the environmental data in each of the environmental data sets are sorted to obtain a time series data set corresponding to each of the devices to be managed;

[0019] Each of the environmental data is monitored according to each of the time series data sets.

[0020] In one embodiment, before the step of determining the target device according to the management decision, the method further includes:

[0021] When it is detected that the changed environmental data is image data, determining whether there is a human portrait in the image data;

[0022] If it is determined that there is a human portrait in the image data, determining the number of human portraits in the image data;

[0023] When it is detected that the number of portraits in the image data is one, the portrait is compared with each preset reference portrait to obtain a target portrait that matches the portrait;

[0024] Adjusting the management decision according to preset preference and habit information corresponding to the target person portrait;

[0025] The step of determining the target device according to the management decision comprises:

[0026] A target device is determined in each of the devices to be managed according to the adjusted management decision.

[0027] In one embodiment, after the step of controlling the target device based on the management decision, the method further includes:

[0028] In response to the voice command output by the target person portrait, each of the devices to be managed is managed according to the voice command, and the preference habit information corresponding to the target person portrait is updated according to the voice command.

[0029] In addition, to achieve the above purpose, the present application also proposes a device management system, which includes:

[0030] A data acquisition module is used to acquire the environmental data collected by each device to be managed and monitor the environmental data;

[0031] A decision generation module, for inputting the current environmental data into a preset intelligent agent when it is detected that there is changed environmental data in each of the environmental data, and obtaining a management decision output by the intelligent agent, wherein the intelligent agent is pre-built based on a large language model;

[0032] The device control module is used to determine the target device according to the management decision and control the target device based on the management decision.

[0033] In addition, to achieve the above objectives, the present application also proposes a computer device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the device management method described above.

[0034] In addition, to achieve the above objectives, the present application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the device management method described above are implemented.

[0035] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the device management method described above are implemented.

[0036] In an embodiment of the present application, by acquiring environmental data collected by each device to be managed and monitoring each environmental data, the environment can be perceived autonomously; then, when it is detected that there is changed environmental data in each environmental data, each environmental data is input into a preset intelligent agent to obtain a management decision output by the intelligent agent, wherein the intelligent agent is pre-constructed based on a large language model, and can automatically generate management decisions that match the environment based on the environment on the premise of autonomously perceiving changes in the environment; then, the target device can be determined in each device to be managed based on the management decision, and the target device can be controlled based on the management decision, so that management of each device can be achieved through the management decision given autonomously by the intelligent agent.

[0037] It can be seen that compared with the traditional method of manually setting equipment control rules for the environment, the present application uses an intelligent agent to achieve autonomous environmental perception and equipment control, which can greatly reduce the time for manual rule setting and thus reduce the management cost of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] 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.

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0040] Figure 1 A flowchart of the first embodiment of the device management method of the present application is provided;

[0041] Figure 2 A flowchart of the third embodiment of the device management method of the present application is provided;

[0042] Figure 3 A schematic diagram of a collaborative process of multiple intelligent agents provided in an embodiment of a device management method of the present application;

[0043] Figure 4 This is a schematic diagram of the module structure of the device management system according to an embodiment of the present application;

[0044] Figure 5 A schematic diagram of the device structure of the hardware operating environment involved in the device management method in the embodiment of the present application.

[0045] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0046] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0047] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0048] Nowadays, with the development of intelligent technology, devices in most scenarios can be managed intelligently. However, traditional intelligent management technology is limited by rules, that is, each scenario is designed in advance, and then a set of rules is designed for each scenario. After accurately identifying the scenario, the device can be managed using the rules corresponding to the scenario. It can be seen that when managing devices through traditional intelligent management technology, it takes a lot of time to set up multiple scenarios and the corresponding rules for multiple scenarios, which makes the management cost of the device relatively high.

[0049] Therefore, how to reduce the management cost of equipment is a technical problem that needs to be solved by those skilled in the art.

[0050] To solve the above problems, the present application can autonomously perceive the environment by acquiring the environmental data collected by each device to be managed and monitoring each environmental data; then, when it is detected that there is changed environmental data in each environmental data, each environmental data is input into a preset intelligent agent to obtain a management decision output by the intelligent agent, wherein the intelligent agent is pre-constructed based on a large language model, and can automatically generate management decisions that match the environment based on the environment on the premise of autonomously perceiving changes in the environment; then, the target device can be determined in each device to be managed based on the management decision, and the target device can be controlled based on the management decision, so that the management of each device can be achieved through the management decision given autonomously by the intelligent agent.

[0051] It can be seen that compared with the traditional method of manually setting equipment control rules for the environment, the present application uses an intelligent agent to achieve autonomous environmental perception and equipment control, which can greatly reduce the time for manual rule setting and thus reduce the management cost of the equipment.

[0052] It should be noted that the execution subject of the device management method of the present application may be a computer device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a server, etc. The following takes a server as an example to illustrate various embodiments of the device management method of the present application.

[0053] Based on this, the present application embodiment provides a device management method, referring to Figure 1 , Figure 1 This is a flowchart of the first embodiment of the device management method of the present application.

[0054] In this embodiment, the device management method includes steps S10 to S30:

[0055] Step S10, obtaining environmental data collected by each device to be managed, and monitoring each of the environmental data;

[0056] It is understandable that in automation scenarios such as smart homes and smart cities, in order to perceive changes in the environment, multiple devices are usually set up in the scenarios that require automated responses, such as home appliances, sensors, etc. Based on this, the devices to be managed in this application are all devices involved in the automated response scenario, and environmental data refers to the data collected by the devices to be managed and the operating parameters of the devices to be managed during operation.

[0057] In this embodiment, in order to avoid wasting computing resources, after obtaining the environmental data, the environmental data is also monitored to determine whether the environmental data has changed. Then, when changes in the environmental data are detected, corresponding decisions can be made according to the specific changes in the environment.

[0058] Specifically, in a feasible implementation manner, the above step S10 includes:

[0059] Step S101, dividing the environmental data belonging to the same device to be managed into a group, and obtaining the environmental data sets corresponding to each of the devices to be managed;

[0060] It is understandable that for the data collected by each device to be managed, the environmental data collected by the same device at different times can be grouped into one group based on the collection device. Thus, the environmental data set corresponding to each device to be managed can be obtained;

[0061] Step S102, sorting the environmental data in each of the environmental data sets based on the collection time corresponding to each of the environmental data sets, to obtain a time series data set corresponding to each of the devices to be managed;

[0062] It is understandable that after obtaining each environmental data set, the environmental data belonging to the same environmental data set can be sorted in ascending order of the collection time according to the collection time corresponding to each environmental data, so that the environmental data in each environmental data set are sorted according to the collection time. After detecting that the environmental data in all environmental data sets have been sorted, the sorted environmental data sets can be used as time series data sets.

[0063] Step S103: monitor each of the environmental data according to each of the time series data sets.

[0064] In this embodiment, after obtaining each time series data set, two adjacent environmental data can be compared in sequence for each time series data set to determine whether there is changed environmental data. Thus, when a change in environmental data is detected, the intelligent agent can be triggered to make a management decision.

[0065] Step S20, when it is detected that there is changed environmental data in each of the environmental data, the environmental data at the current moment is input into a preset intelligent agent to obtain a management decision output by the intelligent agent, wherein the intelligent agent is pre-built based on a large language model;

[0066] It should be noted that management decision refers to the method used to manage equipment. For example, the management decision can be to adjust the air conditioner to 26 degrees Celsius, etc. The intelligent agent can be a model that has the ability to output management decisions based on environmental data, or it can be an AI Agent.

[0067] Step S30: determining a target device according to the management decision, and controlling the target device based on the management decision.

[0068] It should be noted that the target device refers to the device that needs to be parameter adjusted in the management decision. In a feasible implementation, the target device may be one or more of the devices to be managed, and this application does not limit this.

[0069] In this embodiment, after the intelligent agent makes a judgment on the current environment and gives a management decision, the target device can be determined from all devices in the environment according to the specific content of the management decision, and then the target device can be controlled according to the parameter adjustment content in the management decision.

[0070] For example, when an air conditioner and a temperature sensor are provided in an automated environment, if it is detected that the temperature data collected by the temperature sensor changes, the air conditioner parameters and temperature data at this time can be transmitted to the intelligent agent so that the intelligent agent can make a management decision. After the management decision is obtained, the target device can be determined according to the management decision. For example, the target device can be an air conditioner, and then the parameters of the air conditioner can be adjusted according to the specific content of the management decision so that the adjusted air conditioner parameters can match the current environment.

[0071] In a feasible implementation manner, the above step S30 includes:

[0072] Step S301, obtaining a preset interface corresponding to the target device, and constructing a control instruction according to the management decision;

[0073] It is understandable that when modifying the parameters of a device, an interface for modifying the parameters needs to be set for each device. Therefore, for each device, an interface for modifying the operating parameters is preset. Therefore, after determining the target device, the interface corresponding to the target device can be obtained.

[0074] Then, since the parameters of the target device need to be modified through management decisions, control instructions for controlling the target device also need to be constructed according to the management decisions.

[0075] Step S302: transmitting the control instruction to the target device through the interface, so that the target device adjusts parameters based on the control instruction.

[0076] In this embodiment, after obtaining the control instruction and interface of the target device, the control instruction can be transmitted to the target device through the interface so that the target device adjusts its own parameters according to the received control instruction. It can be understood that in this embodiment, the number of control instructions is the same as the number of target devices.

[0077] In an embodiment of the present application, by acquiring environmental data collected by each device to be managed and monitoring each environmental data, the environment can be perceived autonomously; then, when it is detected that there is changed environmental data in each environmental data, each environmental data is input into a preset intelligent agent to obtain a management decision output by the intelligent agent, wherein the intelligent agent is pre-constructed based on a large language model, and can automatically generate management decisions that match the environment based on the environment on the premise of autonomously perceiving changes in the environment; then, the target device can be determined in each device to be managed based on the management decision, and the target device can be controlled based on the management decision, so that management of each device can be achieved through the management decision given autonomously by the intelligent agent.

[0078] It can be seen that compared with the traditional method of manually setting equipment control rules for the environment, the present application uses an intelligent agent to achieve autonomous environmental perception and equipment control, which can greatly reduce the time for manual rule setting and thus reduce the management cost of the equipment.

[0079] Furthermore, based on the above-mentioned first embodiment of the device management method of the present application, a second embodiment of the device management method of the present application is proposed.

[0080] In this embodiment, before the above step S20, the method further includes:

[0081] Step S100, training a preset intelligent agent through prior data to obtain a trained intelligent agent, wherein the prior data is an instruction input by a user;

[0082] It is understandable that the intelligent agent in the first embodiment has the ability to analyze data and generate management decisions based on the data analysis results. In this embodiment, for the intelligent agent that already has the ability to analyze data and generate management decisions, the natural language instructions input by the user can be used as prior knowledge to reduce the training time of the intelligent agent, so that a high-quality intelligent agent can be obtained efficiently.

[0083] Step S200, using each set of preset actual environment data as model input data, using the real management decisions corresponding to each set of actual environment data as model training labels, and training the preset intelligent agent to obtain a trained intelligent agent.

[0084] It should be noted that actual environmental data refers to environmental data collected in advance and used to train intelligent agents, and real management decisions refer to management decisions determined in advance by technical personnel based on actual environmental data.

[0085] In this embodiment, in addition to training the intelligent agent based on prior knowledge, the intelligent agent can also be trained through actual environmental data and real management decisions, thereby improving the ability of the intelligent agent to make correct management decisions.

[0086] In this embodiment, the present application can further improve the ability of the intelligent agent to make correct management decisions by training the intelligent agent that already has the ability to analyze data and generate management decisions, thereby improving the efficiency of equipment management.

[0087] Furthermore, based on the above-mentioned first embodiment and / or second embodiment of the device management method of the present application, a third embodiment of the device management method of the present application is proposed.

[0088] Please refer to Figure 2 In this embodiment, before the above step S30, the method further includes:

[0089] Step S300, when it is detected that the changed environmental data is image data, determining whether there is a human portrait in the image data;

[0090] It is understandable that when a sensor such as a camera that can be used to collect images is provided in an automated scene, the environmental data collected by the camera is the image data. In order to save energy and adapt to the user's usage habits, when it is detected that the changed environmental data is image data, it can be determined whether there is a portrait in the image data by means of target detection or the like.

[0091] Step S400, if it is determined that there are portraits in the image data, then determining the number of portraits in the image data;

[0092] It is understandable that when there are multiple portraits in the image data, it can be determined based on the number of portraits whether adaptive adjustment needs to be made to the management decision based on the user.

[0093] Step S500, when it is detected that the number of portraits in the image data is one, the portrait is compared with each preset reference portrait to obtain a target portrait that matches the portrait;

[0094] It should be noted that the reference portrait is a portrait of a person whose preferences and habits have been acquired, and the target portrait is a reference portrait that matches the portrait information actually collected by the camera.

[0095] Step S600, adjusting the management decision according to preset preference and habit information corresponding to the target portrait;

[0096] Based on this, the above step S30 further includes:

[0097] A target device is determined in each of the devices to be managed according to the adjusted management decision.

[0098] It is understandable that the management decision output by the intelligent agent is suitable for most automation scenarios. The present application can also improve the user experience and build a personalized device management technology by adjusting the management decision output by the intelligent agent through the specific preference and habit information of the portrait.

[0099] Furthermore, in a feasible implementation manner, after the above step S30, the method further includes:

[0100] Step S700, in response to the voice command output by the target person portrait, managing each of the devices to be managed according to the voice command, and updating the preference habit information corresponding to the target person portrait according to the voice command.

[0101] It is understandable that after adaptively adjusting the management decision based on the target person in the current environment, if a voice command output by the target person is received, the voice command can be responded to first. That is, each device to be managed is first managed according to the adjustment information represented by the voice command. Then, the preference and habit information of the target person can be updated according to the voice command, so that a management decision adapted to the target person can be generated based on the updated preference and habit information.

[0102] In this embodiment, the present application can construct personalized management decisions through image data collected by image sensors such as cameras, thereby improving the user experience.

[0103] Furthermore, based on the above-mentioned embodiments of the device management method of the present application, a specific embodiment of the device management method of the present application is proposed.

[0104] Please refer to Figure 3 , Figure 3 A schematic diagram of the collaborative process of multiple agents provided for an embodiment of the device management method of the present application. In this embodiment, the device management method is applied to multiple agents (agents 1 to 6). Specifically, agent 1 can be used for device status monitoring, and its specific function is to obtain the device information (online, offline, open, closed, etc.) of the current conference room in real time, and output it to the environment in a certain data format. Agent 2 can be used for environmental information monitoring, and its specific function is to obtain various information of the current conference room (temperature, light, whether there are people, etc.) in real time, and output it to the environment in a certain data format. Agent 3 can be used for the operation of the smart conference room, and its specific function is to summarize the environmental changes, operation logs, etc. based on all the information in the current smart conference room environment. Agent 4 can be used for control planning, and its specific function is to obtain information provided by other agents from the environment, and plan which device control agents need to be called to control the environment (equivalent to generating management decisions) based on the current information and goals (such as set rules), and feed the results back to the environment. Specifically, agent 4 can also include agent 5 and agent 6. Among them, agent 5 is used for temperature control, and mainly controls specific temperature-related equipment based on the current information and tasks provided by the control planning agent; agent 6 is used for lighting control, and can control specific lighting-related equipment based on the current information and tasks provided by the control planning agent.

[0105] For example, when the goal is: "When someone enters the conference room, the lights should be turned on; when there is no one in the conference room, the lights and air conditioner should be turned off; when the air conditioner is in operation, adjust the appropriate temperature and mode according to the season, weather, outdoor environment, and indoor environment; when there are 10 minutes left before the meeting starts, please make sure the curtains are drawn, the lights are on, and the large screen is turned on", the collaborative results between the various intelligent agents can be: "At 9:36 am, someone entered the conference room and the lights were turned on; the air conditioning temperature has been adjusted to 26°C; at 10:24 am, there was no one in the conference room, the lights were turned off, and the air conditioner was turned off; at 3:20 pm, there were 10 minutes left before the meeting review meeting, the curtains were drawn, the lights were turned on, and the large screen was turned on".

[0106] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the device management method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0107] This application also provides a device management system, please refer to Figure 4 , the equipment management system comprises:

[0108] The data acquisition module 10 is used to acquire the environmental data collected by each device to be managed and monitor the environmental data;

[0109] A decision generation module 20 is used to input the current environmental data into a preset intelligent agent when it is detected that there is a changed environmental data in each of the environmental data, and obtain a management decision output by the intelligent agent, wherein the intelligent agent is pre-built based on a large language model;

[0110] The device control module 30 is used to determine the target device according to the management decision and control the target device based on the management decision.

[0111] In one embodiment, the device control module 30 is further configured to:

[0112] Obtaining a preset interface corresponding to the target device, and constructing a control instruction according to the management decision;

[0113] The control instruction is transmitted to the target device through the interface, so that the target device adjusts parameters based on the control instruction.

[0114] In one embodiment, the device management system further includes:

[0115] A first training module is used to train a preset intelligent agent through prior data to obtain a trained intelligent agent, wherein the prior data is an instruction input by a user;

[0116] The second training module is used to train the preset intelligent agent using the preset groups of actual environmental data as model input data and the real management decisions corresponding to each group of actual environmental data as model training labels to obtain a trained intelligent agent.

[0117] In one embodiment, the data acquisition module 10 is further used for:

[0118] Divide the environmental data belonging to the same device to be managed into a group, and obtain the environmental data sets corresponding to each of the devices to be managed;

[0119] Based on the collection time corresponding to each of the environmental data, the environmental data in each of the environmental data sets are sorted to obtain a time series data set corresponding to each of the devices to be managed;

[0120] Each of the environmental data is monitored according to each of the time series data sets.

[0121] In one embodiment, the device management system further includes:

[0122] A portrait recognition module, for determining whether a portrait exists in the image data when detecting that the changed environmental data is image data;

[0123] a quantity calculation module, configured to determine the number of human portraits in the image data if it is determined that there are human portraits in the image data;

[0124] A portrait matching module, for comparing the portrait with preset reference portraits to obtain a target portrait that matches the portrait when the number of portraits in the image data is detected to be one;

[0125] A strategy adjustment module, used to adjust the management decision according to preset preference and habit information corresponding to the target portrait;

[0126] Based on this, the above-mentioned device control module 30 is also used for:

[0127] A target device is determined in each of the devices to be managed according to the adjusted management decision.

[0128] In one embodiment, the device management system further includes:

[0129] The preference information updating module is used to respond to the voice instruction output by the target person portrait, manage each of the devices to be managed according to the voice instruction, and update the preference habit information corresponding to the target person portrait according to the voice instruction.

[0130] The equipment management system provided by the present application adopts the equipment management method in the above embodiment, which can solve the technical problem of how to reduce the management cost of equipment. Compared with the prior art, the beneficial effects of the equipment management system provided by the present application are the same as the beneficial effects of the equipment management method provided by the above embodiment, and other technical features in the equipment management system are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0131] The present application provides a computer device, which includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the device management method in the above-mentioned embodiment one.

[0132] Reference below Figure 5 , which shows a schematic diagram of the structure of a computer device suitable for implementing an embodiment of the present application. Figure 5 The computer device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0133] like Figure 5As shown, the computer device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the computer device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the computer device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a computer device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0134] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0135] The computer device provided by the present application adopts the device management method in the above embodiment to solve the technical problem of how to reduce the management cost of the device. Compared with the prior art, the beneficial effects of the computer device provided by the present application are the same as the beneficial effects of the device management method provided by the above embodiment, and the other technical features in the computer device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0136] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0137] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0138] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the device management method in the above-mentioned embodiment.

[0139] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0140] The computer-readable storage medium may be included in the computer device; or may exist independently without being installed in the computer device.

[0141] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by a computer device, the computer device: obtains the environmental data collected by each device to be managed, and monitors each environmental data; when it is detected that there is changed environmental data in each environmental data, the environmental data at the current moment is input into a preset intelligent agent to obtain a management decision output by the intelligent agent, wherein the intelligent agent is pre-constructed based on a large language model; determines the target device according to the management decision, and controls the target device based on the management decision.

[0142] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0143] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0144] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0145] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned device management method, and can solve the technical problem of how to reduce the management cost of the device. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the device management method provided in the above-mentioned embodiment, and will not be repeated here.

[0146] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned device management method when executed by a processor.

[0147] The computer program product provided by this application can solve the technical problem of how to reduce the management cost of equipment. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the equipment management method provided by the above embodiment, which will not be repeated here.

[0148] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A device management method, characterized in that: The device management method comprises: Acquire environmental data collected by each device to be managed, and monitor each of the environmental data; When it is detected that there is changed environmental data in each of the environmental data, the environmental data at the current moment is input into a preset intelligent agent to obtain a management decision output by the intelligent agent, wherein the intelligent agent is pre-built based on a large language model; A target device is determined according to the management decision, and the target device is controlled based on the management decision.

2. The device management method according to claim 1, characterized in that: The step of controlling the target device based on the management decision comprises: Obtaining a preset interface corresponding to the target device, and constructing a control instruction according to the management decision; The control instruction is transmitted to the target device through the interface, so that the target device adjusts parameters based on the control instruction.

3. The device management method according to claim 1, characterized in that: Before the step of inputting the current environmental data into a preset intelligent agent to obtain the management decision output by the intelligent agent, the method further includes: Training a preset intelligent agent through prior data to obtain a trained intelligent agent, wherein the prior data is an instruction input by a user; or, The preset groups of actual environmental data are used as model input data, and the real management decisions corresponding to each group of actual environmental data are used as model training labels. The preset intelligent agent is trained to obtain a trained intelligent agent.

4. The device management method according to claim 1, characterized in that: The step of monitoring each of the environmental data comprises: Divide the environmental data belonging to the same device to be managed into a group, and obtain the environmental data sets corresponding to each of the devices to be managed; Based on the collection time corresponding to each of the environmental data, the environmental data in each of the environmental data sets are sorted to obtain a time series data set corresponding to each of the devices to be managed; Each of the environmental data is monitored according to each of the time series data sets.

5. The device management method according to claim 1, characterized in that: Before the step of determining the target device according to the management decision, the method further includes: When it is detected that the changed environmental data is image data, determining whether there is a human portrait in the image data; If it is determined that there is a human portrait in the image data, determining the number of human portraits in the image data; When it is detected that the number of portraits in the image data is one, the portrait is compared with each preset reference portrait to obtain a target portrait that matches the portrait; Adjusting the management decision according to preset preference and habit information corresponding to the target person portrait; The step of determining the target device according to the management decision comprises: A target device is determined in each of the devices to be managed according to the adjusted management decision.

6. The device management method according to claim 5, characterized in that: After the step of controlling the target device based on the management decision, the method further includes: In response to the voice command output by the target person portrait, each of the devices to be managed is managed according to the voice command, and the preference habit information corresponding to the target person portrait is updated according to the voice command.

7. A device management system, characterized in that: The equipment management system comprises: A data acquisition module is used to acquire the environmental data collected by each device to be managed and monitor the environmental data; A decision generation module, for inputting the current environmental data into a preset intelligent agent when it is detected that there is changed environmental data in each of the environmental data, and obtaining a management decision output by the intelligent agent, wherein the intelligent agent is pre-built based on a large language model; The device control module is used to determine the target device according to the management decision and control the target device based on the management decision.

8. A computer device, characterized in that: The computer device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the device management method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the device management method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the device management method according to any one of claims 1 to 6 are implemented.

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