CN111414541A - Equipment recommendation method, device and system - Google Patents
Equipment recommendation method, device and system Download PDFInfo
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Abstract
The invention discloses a device recommendation method, a device and a system, wherein the method comprises the following steps: respectively acquiring a plurality of parameter weight values of equipment; determining recommendation information of the equipment according to the plurality of parameter weight values and equipment operation information, wherein the equipment operation information comprises: the number of days of operation and the operating parameters of the day of operation; and generating device configuration information based on a predetermined rule and according to the recommendation information of the device so as to promote the device according to the device configuration information. The invention can more effectively popularize equipment.
Description
Technical Field
The invention relates to the field of data processing, in particular to a device recommendation method, device and system.
Background
At present, in the face of the marketization impact of the banking industry, a head office and each branch exchange explores how to change, discusses the future trend of a network, and each branch exchange makes active attempts on the advancing road, and a plurality of novel devices are introduced, some of which are used for improving the business handling efficiency and some of which are used for attracting customers to shops.
For the value and the generalizable granularity of the equipment, currently, the estimation can be carried out only by means of offline visits or public praise of business personnel, useless equipment is easily and wrongly popularized, and useful equipment beneficial to banks and customers is easily buried.
Disclosure of Invention
In view of the above, the present invention provides a device recommendation method, apparatus and system to solve at least one of the above-mentioned problems.
According to a first aspect of the present invention, there is provided a device recommendation method, the method comprising: respectively acquiring a plurality of parameter weight values of equipment; determining recommendation information of the equipment according to the parameter weight values and equipment operation information, wherein the equipment operation information comprises: the number of days of operation and the operating parameters of the day of operation; generating device configuration information based on a predetermined rule and according to recommendation information of the device, so as to promote the device according to the device configuration information.
According to a second aspect of the present invention, there is provided a device recommendation apparatus, the apparatus comprising: a weight value obtaining unit for respectively obtaining a plurality of parameter weight values of the device; a recommendation information determination unit, configured to determine recommendation information of the device according to the plurality of parameter weight values and device operation information, where the device operation information includes: the number of days of operation and the operating parameters of the day of operation; and the configuration information generating unit is used for generating equipment configuration information based on a preset rule and according to the recommendation information of the equipment.
According to a third aspect of the present invention, there is provided a device recommendation system, the system comprising: camera equipment, thing networking platform, a plurality of equipment and foretell device.
According to a fourth aspect of the present invention, there is provided an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the above method when executing the program.
According to a fifth aspect of the invention, the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the above-mentioned method.
According to the technical scheme, the recommendation information of the equipment is determined according to the obtained parameter weight value and the equipment operation information of the equipment, and the equipment configuration information is generated by combining the preset rule and the equipment recommendation information, so that the equipment is popularized according to the equipment configuration information.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of a device recommendation method according to an embodiment of the invention;
FIG. 2 is a schematic flow chart of an exemplary business system operation according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a source of device parameter acquisition based on the system of FIG. 2;
FIG. 4 is a block diagram of an architecture of a device recommendation system according to an embodiment of the present invention;
fig. 5 is a block diagram of the configuration of the device recommendation apparatus 1 according to the embodiment of the present invention;
fig. 6 is a block diagram of the structure of the recommendation information determining unit 12 according to an embodiment of the present invention;
fig. 7 is a detailed configuration block diagram of the device recommendation apparatus 1 according to the embodiment of the present invention;
FIG. 8 is a schematic diagram of an electronic device according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, most of equipment placement and deployment application functions in a novel network point depend on the requirements of a bank prison or the reference of other network points, and the popularization of the equipment depends on offline statistics or other public praise decision making, so that the effectiveness of equipment popularization is low, useless equipment is easy to wrongly popularize, and the equipment which is beneficial to banks and customers is easy to bury. Based on this, the embodiment of the invention provides an equipment recommendation scheme so as to improve the effectiveness of equipment popularization. Embodiments of the present invention are described in detail below with reference to the accompanying drawings.
Fig. 1 is a flowchart of a device recommendation method according to an embodiment of the present invention, as shown in fig. 1, the method including:
The parameters herein may include: location information, access volume, operational information, customer service information, etc.
The position information and the access amount of the equipment can be acquired by the camera equipment; the operation information of the equipment can be acquired through the technology of the Internet of things; customer service information may be determined by stored customer information and based on user profiling techniques.
In actual operation, the weight values may be set in advance for the plurality of parameters based on a weight setting rule, respectively. The weight setting rule is set based on the device use weight, the use weight refers to the proportion of the device occupied by human or object interaction, and the larger the weight is, the higher the use value of the device is. For example, the weight of the device access amount is set to be increased along with the increase of the visitor number proportion, and the specific weight value can be determined according to the actual situation.
Specifically, a parameter weight average value may be determined according to the plurality of parameter weight values; determining a recommendation factor according to the operation days, the equipment release number and the operation parameters on the operation day; and then, determining the recommendation information according to the parameter weight average value and the recommendation factor.
Wherein determining the recommendation information according to the parameter weight average and the recommendation factor comprises: determining daily recommendation information according to the quotient of dividing the parameter weight average by the recommendation factor; recommendation information within a predetermined period (e.g., 365 days, one year) is determined from the daily recommendation information and the predetermined period.
The recommendation information of the equipment is determined according to the obtained parameter weight value and the equipment running information of the equipment, and the equipment configuration information is generated by combining the preset rule and the equipment recommendation information, so that the equipment is popularized according to the equipment configuration information.
For a better understanding of embodiments of the present invention, a number of parameters of the device are described in detail below in conjunction with fig. 2 and 3 based on banking.
FIG. 2 is a schematic flow chart of an exemplary business system according to an embodiment of the present invention, as shown in FIG. 2, the business system includes: an internet of things platform 21 (shown as internet of things in the figure), a biometric identification platform 22, a new generation application integration platform (ESB)23, a website management center 24, a client business recommendation component 25 (shown as business recommendation in the figure), a big data management platform 26 (shown as big data in the figure), and a device 27, wherein:
the internet of things platform 21 is a device instruction sending end.
And the biological identification platform 22 is responsible for identifying the biological information of the client.
The new generation application integration platform (ESB)23, is the most basic connection hub in the network.
The network management center 24 is responsible for equipment change process generation points and information collection points.
A client merchant recommendation component 25 for obtaining a customer representation based on the customer information.
And the big data management platform 26 is responsible for generating a big data analysis result according to different contact characteristic information.
The device side 27, which is an information collecting side, is responsible for the client to obtain the change notification contact point.
As shown in fig. 2, the device side 27 requests the biometric platform 22 to perform biometric identification, and the biometric platform 22 performs biometric identification on the device side to obtain biometric information of the client. The equipment end 27 triggers the website management center 24 through a touch point, the website management center 24 acquires a customer portrait from a customer business recommendation component 25 for acquiring a customer business, the website management center 24 performs characteristic analysis according to the acquired customer portrait and requests the big data management platform 26 to perform big data analysis, the big data management platform 26 returns a data analysis result to the website management center 24, the website management center 24 generates an equipment change flow based on the returned result and requests the Internet of things platform 21 to perform equipment control, the Internet of things platform 21 issues a control message to the equipment end 27, the equipment end 27 performs equipment application or state change, and the website management center 24 sends the collected data to the big data management platform 26 for data analysis.
According to the above description, the client information and the physical characteristics of the equipment are obtained, the contact characteristics are analyzed through big data, the equipment change flow is finally generated, and then the internet of things control equipment is used for displaying the equipment in a client demand state or a real-time optimal utilization state.
Fig. 3 is a schematic diagram of a device parameter acquisition source based on the system shown in fig. 2, and as shown in fig. 3, the device parameters include: device location information, device access volume, device service attributes, device operation information, customer business information, and other channel information, each of which is described in detail below.
(1) Device location information
A website can be divided into a plurality of logic areas by a website management center, each area carries customer access traffic (a behavior track of a customer at the website is calculated by face recognition, and if a track route passes through the area for a plurality of times, the traffic of the area is large), equipment position information (for example,1) With regional superiority, the weighting value increases.
In the embodiment of the present invention, the device may be an interactive or non-interactive device, such as a touch screen or a smart television. The devices are intelligent devices, and can switch application states or display states in the application at any time. For example, application state switching: pdf newspaper, exe- > product selling, exe; switching display states in the application: universal video advertisement- > other advertisements targeted to the current user.
It should be noted that the weight value may be set according to actual situations, and only the change rate needs to be presented.
(2) Device access volume
The face recognition camera is installed in the equipment end or the administration area where the equipment is located, and the customer can use the equipment in the modes of card swiping, card swiping and face recognition, so that the access amount is accumulated. Device access volume(for example,2) The weight value of (a) increases as the visitor rate increases.
(3) Device service attributes
Device business attributes include device lifecycle management, such as quantitative data for device procurement processes, quotes, deployments, warranties, and repairs, device business attributes (e.g.,3) And the reverse complexity is increased in sequence according to the service attribute of the equipment.
For example, a device has a high price and is difficult to implement (the input of manpower and material resources before the device is used is large), which means that the device should be able to solve the practical problem of the customer more, the number of times that the device should be used by the customer is larger in an ideal state, if the input is large but the use frequency is low, the return rate of the device is low, otherwise, the return rate of the device is high.
(4) Device operation information
The equipment operation information comprises daily operations of the equipment, such as startup and shutdown, card adding, shield adding, paper adding, bill adding and the like, and the operation times of the relevant equipment are accumulated once every time the operation is performed. The device operation information (e.g.,4) Increasing as the proportion of the number of device operations increases.
(5) Customer information
The device side can acquire basic attributes of the access client, such as an AUM (Asset Management, here, mainly referred to as an Asset of an individual client being delivered) value, age, VIP attribute, and the like, to determine the weight of the client information through an authentication step. The AUM value in the client information (e.g.,5) The weight of (1) increases as the client AUM value increases; the age (e.g.,6) The weight of the young and the young are distributed normally by taking age as a horizontal axis, the weight of the young and the young is slightly higher, and the weight of the young and the old is slightly lower; the VIP level (e.g.,7) The weights of (c) increase with VIP level.
(6) Client business information
According to big data analysis, each customer has partial business opportunities in banking industry, such as opening short messages, purchasing financial products, opening credit cards and the like. Determining client-merchant information based on the degree of engagement of the client-carrying merchant with the device-having function module (e.g., determining the level of engagement of the client-carrying merchant with the device-having function module，8) The weight value of (a) increases as the degree of engagement increases.
(7) Other information
The base decision basis can be customized, including: a determination condition, a linear condition, a nonlinear condition, a determination result, and the like. The customized basis decision criteria will be automatically added to the device parameters, and their weight values can be set according to the actual situation.
In actual operation, a network management center manages all intelligent devices of a network, uses the internet of things technology with a wider action area as a support, covers specific management of device hardware, device service elements, a device life cycle, device software, man-machine interaction, network processes and the like, and constructs a whole set of complete device directed graph by collecting device contact data, device control data, client portrait data, client business data and the like.
Through the network management center, the application heat, the client operation track and the operation content of the current network equipment can be analyzed based on a plurality of channel data, so that an equipment list with the most value of the network, an equipment providing function view and an application conformity degree view can be analyzed, and a decision maker can conveniently popularize the equipment.
Based on the above device parameters and their weights, the following description will proceed with the example of a banking outlet to describe in detail the calculation process of the device recommendation information.
Assuming that the initial value of the device usage is 1, the weights of the parameters of the device represent the final usage value of the device. In this embodiment, the recommendation information is determined for one year based on a predetermined period, and the recommendation information of the device may be determined based on the following formula:
wherein N represents the number of equipment parameters, L represents the number of equipment released on the day, M represents the number of equipment operating dates, and in this embodiment, M takes the value of 365 (corresponding to the predetermined period being one year);
an operation parameter indicating the day the equipment is operated.
The above formula is a calculation formula for a single device, and 365 days in a predetermined period is taken as a measurement unit, and a final result obtained by calculation can be understood as a recommended value of promotion strength (which may be referred to as a rate of return) obtained by putting the device for 365 days.
For the above formula, process result ① - - (1+2+3+4+5+6+7+8+……+N) And (N), this result is a device usage weight average (i.e., a weight average of a plurality of device parameters) acquired through each channel.
Process results ② -
Since 365 days are not the same day by day for the banking industry, for example, the number of people on Monday is more than that on Sunday, it is necessary to set the operation parameters of the equipment on the current day according to different dates or holidays
For example, for the device 1 (e.g., usable for collecting pension), the day of issuance and the following days of pension use of the device 1 is more frequent, and thus the operating parameters of the device 1 for these days
May be set to a higher value, e.g. 5 months and 5 days for the day of giving pension, then 5 months and 5 days for the operating parameters of the device 1
Can be set as the operating parameters of the 300, 5-month and 6-day equipment 1
Set as the operating parameters of the 200, 5-month, 7-day device 1
Set to 100, etc. The current day operating parameters for the different devices may be set based on historical data.
For this embodiment, the operation parameters of each day in a year need to be set for the equipment, and the specific operation parameters may be set according to the historical usage data of the equipment, and the operation parameters only need to reflect the usage of different equipment on different dates.
The recommendation factor can be calculated based on the operating parameters of the day of operation and the number of devices delivered on the day, and a predetermined period (in this example, 365 days for one year).
The result of dividing the result ① by the result ② is the daily recommended value, and then multiplying by 365 is the recommended value of the year.
The recommendation information of the equipment is determined according to the parameters of the equipment, the release quantity of the equipment per day and the operation parameters, so that the use condition of the equipment can be accurately obtained, and the equipment can be more effectively popularized and configured on the basis.
Based on the equipment configuration information, a network equipment popularization report, a network equipment service capability map, a network equipment access thermodynamic diagram, a network equipment utilization map, a network equipment change influence diagram, a network equipment display application service capability thermodynamic diagram and the like can be generated, and a decision maker can be more intuitively helped to determine a popularization scheme of equipment.
Based on similar inventive concepts, an embodiment of the present invention further provides an apparatus recommendation system, fig. 4 is a block diagram of a structure of the system, and as shown in fig. 4, the system includes: the device recommendation device comprises a device recommendation device 1, a camera device 2, a plurality of devices 3 and an Internet of things platform 4. Preferably, the device recommendation apparatus 1 may be used to implement the flow in the above method embodiment. A plurality of parameters of the device, for example, location information and access amount of the device, can be acquired through the camera device 2, and operation information of the device and the like can be acquired through the internet of things platform 4.
Fig. 5 is a block diagram showing the configuration of the device recommendation apparatus 1, and as shown in fig. 5, the device recommendation apparatus 1 includes: a weight value obtaining unit 11, a recommendation information determining unit 12, and a configuration information generating unit 13, wherein:
a weight value obtaining unit 11, configured to obtain a plurality of parameter weight values of the device, respectively, where the plurality of parameters include: location information, access volume, operation information, customer service information (including customer basic information, customer business information, etc.), device service attributes, etc.
A recommendation information determining unit 12, configured to determine recommendation information of the device according to the plurality of parameter weight values and device operation information, where the device operation information includes: the number of days of operation and the operating parameters of the day of operation;
a configuration information generating unit 13 for generating device configuration information based on a predetermined rule and according to the recommendation information of the device.
The recommendation information of the equipment is determined by the recommendation information determining unit 12 according to the parameter weight value of the equipment and the equipment running information acquired by the weight value acquiring unit 11, and the configuration information generating unit 13 generates the equipment configuration information by combining the predetermined rule and the equipment recommendation information so as to popularize the equipment according to the equipment configuration information.
Specifically, as shown in fig. 6, the recommendation information determining unit 12 includes: a weight average determination module 121, a recommendation factor determination module 122, and a recommendation information determination module 123, wherein:
a weight average determining module 121, configured to determine a parameter weight average according to the plurality of parameter weight values;
the recommendation factor determining module 122 is configured to determine a recommendation factor according to the number of operation days, the number of equipment releases on the current operation day, and the operation parameters;
and a recommendation information determining module 123, configured to determine the recommendation information according to the parameter weight average and the recommendation factor.
The recommendation information determining module 123 includes: a daily recommendation information determination sub-module 1231 and a recommendation information determination sub-module 1232, wherein:
a daily recommendation information determination submodule 1231 configured to determine daily recommendation information according to a quotient obtained by dividing the parameter weight average by the recommendation factor;
and the recommendation information determining submodule 1232 is configured to determine recommendation information in the predetermined period according to the daily recommendation information and the predetermined period.
In actual practice, as shown in fig. 7, the device recommendation apparatus 1 further includes: a device basic information acquisition unit 14, a device operation information acquisition unit 15, a customer information acquisition unit 16, and a weight setting unit 17, wherein:
an apparatus basic information acquisition unit 14 for acquiring position information and an access amount of the apparatus by an image pickup apparatus;
the device operation information acquiring unit 15 is configured to acquire operation information of the device through an internet of things technology;
a client information acquisition unit 16 for determining the client service information by acquiring the stored client information and based on a user profile technique;
a weight setting unit 17 configured to set weight values for the plurality of parameters, respectively, based on a weight setting rule.
For specific execution processes of the units, the modules, and the sub-modules, reference may be made to the description in the foregoing method embodiments, and details are not described here again.
In practical operation, the units, the modules and the sub-modules may be combined or may be arranged singly, and the present invention is not limited thereto.
FIG. 8 is a schematic diagram of an electronic device according to an embodiment of the invention. The electronic device shown in fig. 8 is a general-purpose data processing apparatus comprising a general-purpose computer hardware structure including at least a processor 801 and a memory 802. The processor 801 and the memory 802 are connected by a bus 803. The memory 802 is adapted to store one or more instructions or programs that are executable by the processor 801. The one or more instructions or programs are executed by the processor 801 to implement the steps in the device recommendation method described above.
The processor 801 may be a stand-alone microprocessor or a collection of one or more microprocessors. Thus, the processor 801 implements the processing of data and the control of other devices by executing commands stored in the memory 802 to thereby execute the method flows of embodiments of the present invention as described above. The bus 803 connects the above components together, and also connects the above components to a display controller 804 and a display device and an input/output (I/O) device 805. Input/output (I/O) devices 805 may be a mouse, keyboard, modem, network interface, touch input device, motion sensing input device, printer, and other devices known in the art. Typically, input/output (I/O) devices 805 are connected to the system through an input/output (I/O) controller 806.
The memory 802 may store, among other things, software components such as an operating system, communication modules, interaction modules, and application programs. Each of the modules and applications described above corresponds to a set of executable program instructions that perform one or more functions and methods described in embodiments of the invention.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the steps of the device recommendation method.
In summary, according to the embodiment of the present invention, the final service data provided by the device side is acquired from multiple channels and multiple platforms, and the final service capability of the device is calculated according to the acquired data items, so as to promote the device.
The preferred embodiments of the present invention have been described above with reference to the accompanying drawings. The many features and advantages of the embodiments are apparent from the detailed specification, and thus, it is intended by the appended claims to cover all such features and advantages of the embodiments which fall within the true spirit and scope thereof. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the embodiments of the invention to the exact construction and operation illustrated and described, and accordingly, all suitable modifications and equivalents may be resorted to, falling within the scope thereof.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (13)
1. A device recommendation method, the method comprising:
respectively acquiring a plurality of parameter weight values of equipment;
determining recommendation information of the equipment according to the parameter weight values and equipment operation information, wherein the equipment operation information comprises: the number of days of operation and the operating parameters of the day of operation;
generating device configuration information based on a predetermined rule and according to recommendation information of the device, so as to promote the device according to the device configuration information.
2. The method of claim 1, wherein determining recommendation information for the device based on the plurality of parameter weight values and device operational information comprises:
determining a parameter weight average value according to the plurality of parameter weight values;
determining a recommendation factor according to the operation days, the equipment release number on the operation day and the operation parameters;
and determining the recommendation information according to the parameter weight average value and the recommendation factor.
3. The method of claim 2, wherein determining the recommendation information according to the parameter weight average and the recommendation factor comprises:
determining daily recommendation information according to the quotient of dividing the parameter weight average by the recommendation factor;
and determining recommendation information in the preset period according to the daily recommendation information and the preset period.
4. The method of claim 1, wherein the plurality of parameters comprises: position information, access amount, operation information and customer service information, and the method further comprises the following steps:
acquiring position information and access amount of the equipment through camera equipment;
acquiring operation information of the equipment through the technology of the Internet of things;
the customer service information is determined by retrieving stored customer information and based on user profiling techniques.
5. The method of claim 4, wherein before obtaining the plurality of parameter weight values of the device respectively, the method further comprises:
setting weight values for the plurality of parameters respectively based on a weight setting rule.
6. An apparatus for recommending devices, said apparatus comprising:
a weight value obtaining unit for respectively obtaining a plurality of parameter weight values of the device;
a recommendation information determination unit, configured to determine recommendation information of the device according to the plurality of parameter weight values and device operation information, where the device operation information includes: the number of days of operation and the operating parameters of the day of operation;
and the configuration information generating unit is used for generating equipment configuration information based on a preset rule and according to the recommendation information of the equipment.
7. The apparatus according to claim 6, wherein the recommendation information determining unit includes:
the weight average value determining module is used for determining a parameter weight average value according to the plurality of parameter weight values;
the recommendation factor determining module is used for determining recommendation factors according to the operation days, the equipment release number on the operation day and the operation parameters;
and the recommendation information determining module is used for determining the recommendation information according to the parameter weight average value and the recommendation factor.
8. The apparatus of claim 7, wherein the recommendation information determining module comprises:
the daily recommendation information determining submodule is used for determining daily recommendation information according to the quotient of dividing the parameter weight average value by the recommendation factor;
and the recommendation information determining submodule is used for determining recommendation information in the preset period according to the daily recommendation information and the preset period.
9. The apparatus of claim 6, wherein the plurality of parameters comprise: position information, access amount, operation information, customer service information, the device further comprises:
an apparatus basic information acquisition unit configured to acquire position information and an access amount of the apparatus by an image pickup apparatus;
the equipment operation information acquisition unit is used for acquiring the operation information of the equipment through the Internet of things technology;
and the client information acquisition unit is used for acquiring the stored client information and determining the client service information based on the user portrait technology.
10. The apparatus of claim 9, further comprising:
a weight setting unit configured to set weight values for the plurality of parameters, respectively, based on a weight setting rule.
11. A device recommendation system, the system comprising: an imaging device, an internet of things platform, a plurality of devices, and the apparatus of any of claims 6-10.
12. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1 to 5 are implemented when the processor executes the program.
13. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 5.
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