Business Management Method, Device and Computer Readable Storage Medium of Intelligent Device

Abstract

The present invention discloses a service management method, device and computer-readable storage medium for an intelligent device. The method includes: the intelligent device monitors the service behaviors of its own various services; obtains the service popularity of each service; and allocates services and device resources in combination with the current service behaviors and service popularity. By the above manner, the present invention can improve the utilization rate of device resources and the operation efficiency of device services.

Description

Technical Field

[0001] The present invention relates to the field of electronic technologies, and particularly to a method, device, and computer-readable storage medium for business management of intelligent devices. Background Art

[0002] In today's era, with the development of electronic device technologies, the business functions of devices are becoming increasingly rich. Especially with the emergence of artificial intelligence technologies, various intelligent devices have emerged, such as smart home devices, smart city devices, smart security devices, etc., and each device has its own functional services. When the device functional services become numerous, problems such as unreasonable allocation of device resources and low business work efficiency are likely to occur. Currently, there is no feasible method for the device itself to manage device resources and functional services. Summary of the Invention

[0003] The main technical problem to be solved by the present invention is to provide a method for business management of intelligent devices, which can improve the utilization rate of device resources and the operation efficiency of device services.

[0004] To solve the above technical problem, a technical solution adopted by the present invention is: to provide a method for business management of intelligent devices, the method for business management of intelligent devices including: an intelligent device monitors the business behaviors of its own various services; obtains the business heat of each service; and allocates services and device resources in combination with the current business behaviors and business heat.

[0005] Among them, allocating services and device resources in combination with the current business behaviors and business heat includes: obtaining the proportion of the device resources required by the currently active services in the total device resources to obtain the utilization rate of the device resources. If the utilization rate is less than a preset threshold, then idle services are started.

[0006] Among them, allocating services and device resources in combination with the current business behaviors and business heat includes: sorting the currently active services according to the business heat; and allocating device resources according to the service sequence, the higher the ranking, the better the allocated device resources.

[0007] Among them, allocating services and device resources in combination with the current business behaviors and business heat includes: obtaining the activity of each service within a predetermined time period; predicting the activity of services in the next time period; and allocating device resources in the next time period according to the prediction result.

[0008] Among them, obtaining the business heat of each service includes: obtaining the occurrence times and occurrence times of each service within a predetermined time interval, and calculating the cumulative occurrence times within the predetermined time interval to obtain the business heat of the service.

[0009] Among them, obtaining the business popularity of each service includes: classifying each service and setting a statistical analysis period; respectively performing statistical analysis on services of different time periods and different types, and separately storing the data of each analysis result.

[0010] Among them, the service management method of the intelligent device further includes: receiving a query request for service information; sending the service information of the corresponding service to the requester, and the service information includes one or more of the usage rate, service type, service popularity, and service behavior history record of the queried service.

[0011] To solve the above technical problems, another technical solution adopted by the present invention is: an intelligent device, which includes: a monitoring module for monitoring the service behaviors of its own services; an obtaining module for obtaining the service popularity of each service; and a deployment module for deploying services and device resources in combination with the current service behaviors and service popularity.

[0012] To solve the above technical problems, another technical solution adopted by the present invention is: an intelligent device, which includes a processor for executing instructions to implement the service management method of the above intelligent device.

[0013] To solve the above technical problems, another technical solution adopted by the present invention is: a computer-readable storage medium for storing instructions / program data, and the instructions / program data can be executed to implement the service management method of the above intelligent device.

[0014] The beneficial effect of the present invention is: different from the prior art, the present invention monitors the service behaviors and service popularity of the intelligent device itself, understands the usage of services and the operation of the device itself, and reasonably deploys services and device resources according to the specific situation, improving the utilization rate of device resources and the operation efficiency of device services, and achieving a better device usage effect. Description of the Drawings

[0015] Figure 1 is a flowchart of the service management method of an intelligent device in an embodiment of the present application;

[0016] Figure 2 is a basic service statistical heat map within a time period in an embodiment of the present application;

[0017] Figure 3 is an intelligent service statistical heat map within a time period in an embodiment of the present application;

[0018] Figure 4 is a flowchart of the service management method of another intelligent device in an embodiment of the present application;

[0019] Figure 5It is a schematic flowchart of an intelligent device in an application scenario of an embodiment of the present application;

[0020] Figure 6 It is a schematic flowchart of a first device in an application scenario of an embodiment of the present application;

[0021] Figure 7 It is a schematic structural diagram of a service management device of an intelligent device in an embodiment of the present application;

[0022] Figure 8 It is a schematic structural diagram of an intelligent device in an embodiment of the present application;

[0023] Figure 9 It is a schematic structural diagram of a computer-readable storage medium in an embodiment of the present application. Detailed implementation manners

[0024] To make the objectives, technical solutions and effects of the present invention clearer and more definite, the present invention will be further described in detail below with reference to the accompanying drawings and by way of examples.

[0025] The present application provides a service management method for an intelligent device, which allocates services and device resources by combining the current service behaviors and service popularity, so as to improve the utilization rate of device resources and the operation efficiency of each service. This service management method can be applied to various intelligent devices, such as smart home devices, various devices in a smart city, various devices in intelligent security, etc. For the convenience of description, the service management method of a security monitoring device is taken as an example in the present application for illustration, but it is not limited to this intelligent device.

[0026] Please refer to Figure 1 , Figure 1 It is a schematic flowchart of a service management method of an intelligent device in an embodiment of the present application. It should be noted that if there are substantially the same results, this embodiment is not limited to Figure 1 the process sequence shown. As Figure 1 [[ID=�5]]shown, this embodiment includes:

[0027] S101: The intelligent device monitors the service behaviors of its own services.

[0028] The intelligent device can monitor the service behaviors of its own services. The own services may include real-time monitoring, video recording, video playback, intelligent monitoring, face recognition, behavior recognition, etc. These own services may be in a used state or a non-used state, and the corresponding service behaviors include being active and inactive. The active services need to occupy device resources during operation, and the inactive services do not need to occupy device resources.

[0029] S103: Obtain the service popularity of each service.

[0030] Business heat refers to the activity level of a business. The higher the frequency of business use, the higher the business heat. There are various specific quantification methods for business heat, such as business data statistical tables, business usage heat maps, calculating business usage rates, etc.

[0031] S105: Allocate business and device resources by combining the current business behavior and business heat.

[0032] By understanding the currently active businesses, the usage situation of the device can be understood, and the operation of different businesses can be reasonably allocated according to the usage heat of the device itself, or the load balancing of hardware resources can be carried out to achieve better device usage effects.

[0033] In this embodiment, by monitoring the business behavior and business heat of the intelligent device itself, the usage situation of the business and the operation situation of the device itself are understood, and the business and device resources are reasonably allocated according to the specific situation, improving the utilization rate of device resources and the operation efficiency of device services, and achieving better device usage effects.

[0034] In one embodiment, obtaining the business heat of each business includes classifying, counting, and analyzing the business.

[0035] There are many businesses in intelligent devices, and directly obtaining business heat data is rather cumbersome and the data is messy. Therefore, the businesses of intelligent devices are first classified. Classifying the business helps in the statistics and analysis of business data. Different classification methods can be used for different intelligent devices, and the application does not limit the classification methods used. In this embodiment, to meet the development needs of intelligent devices in the intelligent era, the own businesses of security devices are first divided into two major categories: basic businesses and intelligent businesses, and then the basic businesses and intelligent businesses are classified separately. Separately classifying intelligent businesses allows for separate statistics according to the types of intelligent businesses, facilitating the viewing of the occurrence of intelligent businesses of the device. The main intelligent businesses of security monitoring devices include: face monitoring, face recognition, tripwire intrusion, area intrusion, personnel gathering events, vehicle reverse, passenger flow statistics events, etc. The basic businesses of intelligent devices can be classified according to the major types of businesses. For example, the main basic businesses of security monitoring devices include: device login, real-time monitoring, video playback, pan-tilt control, ordinary alarm, intelligent event alarm, customized business types, etc.

[0036] According to the classification of the smart device business, obtain the occurrence times and occurrence times of each business within a predetermined time interval, and calculate the cumulative occurrence times within the predetermined time interval to obtain the business popularity of the business. Specifically, the time interval for data statistics is preset according to the actual situation. Taking one time interval as a statistical node and the data within one time interval as a set of data, the time interval can be adjusted at any time. The time intervals of each set of data can be the same or different. The time interval can be 1 hour, 2 hours, 1 day, 1 week, etc. Conduct statistics on business data according to the predetermined time interval. When a certain business occurs within the predetermined time interval, record the time when the business occurs. The same business may occur once or multiple times at the same time, and record the number of times the business occurs at that time. When the business is monitored to occur again at the next time point, similarly, record the time and number of times the business occurs, and calculate the cumulative number of times. After the end of the predetermined time interval, count the cumulative occurrence times of the business, and count the occurrence times, occurrence times and cumulative occurrence times of all businesses within this time interval as a set of data. Restart the counting in the next predetermined time interval to obtain a business statistical table or a business heat map. Please refer to Table 1 and Table 2. Table 1 is a statistical table of basic services within a certain period in the embodiment of the present application, and Table 2 is a statistical table of intelligent services within a certain period in the embodiment of the present application. Please refer to Figure 2 and Figure 3 , Figure 2 is the statistical heat map of basic services within a certain period in the embodiment of the present application, Figure 3 is the statistical heat map of intelligent services within a certain period in the embodiment of the present application.

[0037] Table 1 Statistical table of basic services within a certain period in the embodiment of the present application

[0038] Time Device Login Real-time Monitoring Video Playback PTZ Control General Alarm Others 00:00 1 0 0 1 10 2 01:00 2 1 0 1 5 2 02:00 3 2 0 0 5 2 03:00 4 3 0 2 4 2 04:00 5 1 2 0 2 2 05:00 6 1 0 0 1 2 06:00 7 1 0 0 6 2 07:00 8 1 0 0 20 2 08:00 9 1 0 0 0 2

[0039] Table 2 Statistical table of basic services within a certain period in the embodiment of the present application

[0040] Time Face Recognition Face Detection Motion Detection Human Detection Area Intrusion Others 00:00 1 0 10 1 2 2 01:00 2 1 5 1 5 2 02:00 0 2 20 0 10 2 03:00 0 3 0 2 4 2 04:00 5 1 4 0 20 2 05:00 5 5 30 0 1 2 06:00 20 1 0 0 6 2 07:00 2 1 20 0 20 2 08:00 9 0 0 10 0 2

[0041] Based on the service statistics table and service heat map, the usage rate of each service can be calculated, which is more convenient for data analysis in the case of a large number of services. In this embodiment, taking the calculation of the usage rate as an example of service heat, the cumulative number of occurrences of a certain service within a time interval and the cumulative number of occurrences of all services within this time interval are calculated as the usage rate (Usage) of this service. The formula for calculating the usage rate of Service A is: Usage(A) = num(A) / num(Total). The higher the usage rate, the higher the heat. Combining Table 2, within the time period from 1:00 to 2:00, the usage rate of face detection is 5.88%, and the usage rate of dynamic detection is 58.82%. During this time period, the service heat of dynamic monitoring is higher than that of face detection.

[0042] After obtaining the service heat of each service of the intelligent device, the statistical data is analyzed. A statistical analysis period is preset, and after each period ends, the statistical data within the period is analyzed as a whole. The analysis period can be the same as the time interval for statistical collection of service data, or longer than the time interval for statistical collection of service data. Statistical analysis is performed separately for different time periods and different types of services, and the analysis result data is stored separately. According to the statistical results, the service data is analyzed. The usage of various types of active services within the same time period is statistically analyzed to understand the usage of various services during this time period; the usage of the same type of active services within different time periods is statistically analyzed to understand the usage of this service in different time periods. The result data obtained from the analysis is stored separately. In this embodiment, the storage method is not limited. It can be stored according to the time interval. For example, within one day, the usage data is statistically collected every hour, and 24 times of data will be statistically collected every day. It is stored according to the statistical time points to facilitate subsequent data reading and calculation.

[0043] In one embodiment, the allocation of services and device resources in combination with the current service behavior and service heat includes: separately allocating service usage and allocating device resources.

[0044] By understanding the current active services, the usage situation of the device can be understood. According to the usage heat of the device itself, the operation of different services is reasonably allocated, or the load balancing of hardware resources is performed to achieve a better device usage effect. Among the multiple services of the intelligent device, there are services that must be performed after being triggered, and there are also services that can be performed at any time. If there are many current active services or the device resources occupied by the active services are relatively large, idle services such as calculation services and statistical services that do not need to be performed at a specific time can be closed to release device resources for other necessary services. Specifically, the proportion of the device resources required by the current active services in the total device resources is obtained to get the usage rate of the device resources. If the usage rate is less than the preset threshold, the idle service is started; if the usage rate is greater than the preset threshold, the idle service is closed.

[0045] By understanding the business heat of the current business, the device resources used for each business are reasonably allocated. The business with more frequent use requires better device resources. In one implementation, the current active businesses are sorted according to the business heat, and the device resources are allocated according to the business sequence. The higher the ranking, the better the allocated device resources. In another implementation, the business heat can be segmented, which can be divided into two segments or multiple segments. When the business heat is divided into three segments, a first threshold and a second threshold are set. The first threshold is greater than the second threshold. When the business heat of a certain business is greater than or equal to the first threshold, the first resource is allocated. When the business heat of a certain business is greater than or equal to the second threshold and less than the first threshold, the second resource is allocated. When the business heat of a certain business is less than the second threshold, the third resource is allocated. The resource quality of the first resource, the second resource, and the third resource decreases in turn. At the same time, by understanding the frequency of use of each business and the amount of device resources occupied, it is clear which business mainly consumes the device life.

[0046] By understanding the business heat of historical businesses, the device resources used for each business are reasonably allocated. Understanding the usage of the same business in different time periods is convenient for reasonably allocating the device resources of this business. During the long-term use of the same business, its activity has certain rules. By obtaining the activity of each business within the first preset time period, the business activity of the second preset time period is predicted, and the device resources of the second preset time period are allocated according to the prediction result. The interval between the first preset time period and the second preset time period can be equal or unequal. The second preset time period is after the first preset time period, and the two time periods do not overlap. The two time periods can be continuous time periods or non-continuous time periods. At the same time, different time periods can be set for different businesses for prediction. For example, for face monitoring, the activity is high during the peak commuting hours on weekdays and low during working hours. The activity of face monitoring in the corresponding time period of the next working day can be predicted by obtaining the activity of face monitoring in each time period of the previous working day, and the device resources for face monitoring can be allocated in advance. In another implementation, the prediction can be made through the overall data of the previous week's weekdays or the overall data of the previous month's weekdays. The selection of the specific time period can be determined according to the actual situation and is not limited herein.

[0047] Furthermore, by performing data analysis on business behaviors and business heat, the practical significance behind the data is mined. In one implementation, when the human detection heat is relatively high in the same continuous time period, an investigation can be carried out for this time period to determine whether additional security measures are needed for this time period. In another implementation, when the heat of the personnel gathering time is relatively high in the same continuous time period, an investigation can also be carried out for this time period to determine whether it is necessary to clear the passage or open the standby passage during this time period.

[0048] In another embodiment, in order to perform in-depth statistical analysis of the business data of intelligent devices and to facilitate the reading and display of business data, a first device is connected to the intelligent device, and the statistical data can be displayed on the first device. The first device can be a device capable of display such as a mobile phone or a PC computer. By obtaining this information, the value of the mined information can be fully utilized, and it can also intervene in the device resources and business allocation of the intelligent device.

[0049] Refer to Figure 4 , Figure 4 is a schematic flowchart of a business management method for another intelligent device in an embodiment of the present application. It should be noted that if there are substantially the same results, this embodiment is not limited to Figure 4 the process sequence shown. As Figure 4 shown, this embodiment includes:

[0050] S401: The intelligent device monitors the business behaviors of its own various services.

[0051] S403: Obtain the business popularity of each service.

[0052] S405: Receive a query request for business information.

[0053] A first device is connected to the intelligent device. The first device can send a query request to the intelligent device according to specific requirements, or can also send a query request for obtaining all data.

[0054] S407: Send the business information of the corresponding service to the requester.

[0055] The business information includes one or more of the usage rate, service type, business popularity, and business behavior history record of the queried service.

[0056] In this embodiment, by monitoring the business behaviors and business popularity of the intelligent device itself, it is understood which services the device is performing, which services are used more frequently and have a high business popularity. By quantifying the data on the self-running situation of the intelligent device and the usage situation of the services, and reasonably allocating the services and device resources according to specific circumstances, the utilization rate of device resources and the operation efficiency of device services are improved, achieving a better device usage effect. At the same time, the actual life can be managed and adjusted according to specific circumstances, making the management more efficient.

[0057] Please refer to Figure 5 and Figure 6 , Figure 5 is a schematic flowchart of an intelligent device in an application scenario in an embodiment of the present application, Figure 6 is a schematic flowchart of a first device in an application scenario in an embodiment of the present application.

[0058] The intelligent device in this application scenario is intelligent monitoring. The preset statistical time interval is two hours, and the time period for data storage and analysis is four hours. The monitoring camera starts to work and the service monitoring function is enabled. The service monitoring function can be controlled to be turned on and off through the intelligent device or the first device. It starts to monitor whether a service occurs. When a certain service is detected to occur, the time when the service occurs is recorded and the number of times the service occurs is counted. It continuously monitors within the preset two hours and accumulates the number of times the service occurs. The intelligent device classifies and stores the statistical data according to the preset four hours and updates the stored service data. Simple calculation processing can be performed on the data before storage to make the data more convenient for storage.

[0059] The first device is connected to the intelligent device. It selects the time period and service to view according to specific needs, or can also select to view all monitoring information. The first device sends a query request to the intelligent device to obtain the data of the required service, and performs algorithm analysis and calculation on the service data, such as daily active statistics of the service, calculation of the usage frequency of each service, etc. The processed service usage data is displayed on the screen, and the service and device resources are allocated in combination with the current service behavior and service popularity.

[0060] In this embodiment, by monitoring the service behavior and service popularity of the intelligent device itself, the usage situation of the service and the operation situation of the device itself are understood, and the first device is connected to process the data to obtain a deeper analysis result, which can be intuitively displayed. Then, according to the specific situation, the service and device resources are reasonably allocated, improving the utilization rate of device resources and the operation efficiency of device services, and achieving a better device usage effect.

[0061] Please refer to Figure 7 , Figure 7 which is a schematic structural diagram of the service management device of the intelligent device in the embodiment of the present application. In this embodiment, the service management device of the intelligent device includes a monitoring module 71, an acquisition module 72, and a deployment module 73.

[0062] Among them, the monitoring module 71 is used for the intelligent device to monitor the service behaviors of its own various services; the acquisition module 72 is used to obtain the service popularity of each service; the deployment module 73 is used to allocate the service and device resources in combination with the current service behavior and service popularity. Specifically, the acquisition module 72 further includes a self-check control module, a basic service statistics module, and an intelligent service statistics module. The self-check control module is used to set the self-check mode and self-check parameters of the intelligent device, and determine the categories and statistical methods to be counted through configuration or control commands; the basic service statistics module is used for the classification and statistics of basic services; the intelligent service statistics module is used for the classification and statistics of intelligent services.

[0063] Further, the service management device of the intelligent device further includes a data storage module, a logic processing module, and a network transmission module. The data storage module is used for storing statistical data; the logic processing module is used for obtaining, adding, deleting, updating, calculating and processing statistical data and other logic processing; the network transmission module is used for network transmission of information.

[0064] By monitoring the service behavior and service popularity of the intelligent device itself, the usage of the service and the operation of the device itself are understood, and the service and device resources are reasonably allocated according to the specific situation, which improves the utilization rate of device resources and the operation efficiency of device services, and achieves a better device usage effect.

[0065] Please refer to Figure 8 , Figure 8 , which is a schematic structural diagram of the intelligent device in the embodiment of the present application. In this embodiment, the intelligent device 81 includes a processor 82.

[0066] The processor 82 can also be called a CPU (Central Processing Unit). The processor 82 may be an integrated circuit chip with signal processing capabilities. The processor 82 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor 82 can also be any conventional processor, etc.

[0067] The intelligent device 81 can further include a memory (not shown in the figure) for storing instructions and data required for the operation of the processor 82.

[0068] The processor 82 is used to execute instructions to implement the method provided by any embodiment and any non-conflicting combination of the service management methods of the intelligent device of the present application.

[0069] Please refer to Figure 9 , Figure 9It is a schematic structural diagram of a computer-readable storage medium in an embodiment of the present application. The computer-readable storage medium 91 of the embodiment of the present application stores instruction / program data 92, and when the instruction / program data 92 is executed, it implements the method provided by any embodiment of the business management method of the intelligent device of the present application and any non-conflicting combination. Among them, the instruction / program data 92 can form a program file and be stored in the above storage medium 91 in the form of a software product, so that a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor can execute all or part of the steps of the methods of various embodiments of the present application. And the foregoing storage medium 91 includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks or optical discs, or terminal devices such as computers, servers, mobile phones, and tablets.

[0070] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed mutual coupling, direct coupling, or communication connection can be through some interfaces, and the indirect coupling or communication connection of devices or units can be in electrical, mechanical, or other forms.

[0071] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0072] The above is only the embodiment of the present application, and it does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, is equally included in the patent protection scope of the present invention.

Claims

1. A method for business management of an intelligent device, characterized in that, The method includes: The intelligent device monitors the business behaviors of its own various services. Obtain the business heat of each service. Allocate services and device resources by combining the current business behaviors and business heat. Among them, the allocation of services and device resources by combining the current business behaviors and business heat includes: Obtain the activity of each service within a first preset time period. Predict the business activity of a second preset time period based on the activity of each service within the first preset time period, where the second preset time period has an unequal interval from the first preset time period. Allocate the device resources of the second preset time period according to the prediction result.

2. The business management method of the intelligent device according to claim 1, characterized in that The allocation of services and device resources by combining the current business behaviors and business heat includes: Obtain the proportion of the device resources required by the currently active services in the total device resources to obtain the utilization rate of the device resources. If the utilization rate is less than a preset threshold, start the idle services.

3. The business management method of the intelligent device according to claim 1, characterized in that The allocation of services and device resources by combining the current business behaviors and business heat includes: Sort the currently active services according to the business heat. Allocate device resources according to the service sequence. The higher the ranking, the better the allocated device resources.

4. The business management method of the intelligent device according to claim 1, characterized in that, The obtaining of the business heat of each service includes: Obtain the occurrence times and occurrence times of each service within a predetermined time interval, and calculate the cumulative occurrence times within the predetermined time interval to obtain the business heat of the service.

5. The service management method of the intelligent device according to claim 4, characterized in that, The obtaining of the business heat of each service includes: Classify each service and set a statistical analysis period. Conduct statistical analysis on different time periods and different types of services respectively, and store each analysis result data separately.

6. The business management method of the intelligent device according to claim 1, characterized in that, The method further includes: Receive a query request for service information. Send the service information of the corresponding service to the requester. The service information includes one or more of the utilization rate, service type, business heat, and business behavior history record of the queried service.

7. An intelligent device, characterized in that, The intelligent device includes: A monitoring module for the intelligent device to monitor the business behaviors of its own various services. An obtaining module for obtaining the business heat of each service. A deployment module for allocating services and device resources by combining the current business behaviors and business heat. Among them, the allocation of services and device resources by combining the current business behaviors and business heat includes: obtaining the activity of each service within a first preset time period; predicting the business activity of a second preset time period based on the activity of each service within the first preset time period, where the second preset time period has an unequal interval from the first preset time period; allocating the device resources of the second preset time period according to the prediction result.

8. An intelligent device, characterized in that, It includes a processor, and the processor is used to execute instructions to implement the business management method of the intelligent device according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store instructions / program data, and the instructions / program data can be executed to implement the business management method of the intelligent device according to any one of claims 1-6.

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