CN116739664B

CN116739664B - Advertisement pushing method and system based on Internet of things

Info

Publication number: CN116739664B
Application number: CN202311006860.1A
Authority: CN
Inventors: 戴韬
Original assignee: Beijing Jixin Technology Co ltd
Current assignee: Beijing Jixin Technology Co ltd
Priority date: 2023-08-11
Filing date: 2023-08-11
Publication date: 2023-11-21
Anticipated expiration: 2043-08-11
Also published as: CN116739664A

Abstract

The invention relates to the technical field of advertisement pushing, and discloses an advertisement pushing method and system based on the Internet of things, which are used for improving the advertisement pushing accuracy and efficiency of the Internet of things. The method comprises the following steps: setting a first advertisement pushing model of each fixed internet of things advertisement device; creating a target advertisement and a two-dimensional code, carrying out two-dimensional code advertisement putting through a plurality of fixed internet of things advertisement devices, and acquiring user code scanning data and device authorization data; acquiring a plurality of second equipment position information, and performing topology analysis according to the second equipment position information and user code scanning data to obtain a second equipment network topology map; constructing an advertisement push state matrix according to the second equipment network topological graph, inputting the advertisement push state matrix into an advertisement putting strategy optimization model, and generating a second advertisement putting strategy through the advertisement putting strategy optimization model; and setting a second advertisement pushing model according to a second advertisement putting strategy, and pushing advertisements through the second advertisement pushing model.

Description

Advertisement pushing method and system based on Internet of things

Technical Field

The invention relates to the technical field of advertisement pushing, in particular to an advertisement pushing method and system based on the Internet of things.

Background

In conventional advertisement pushing, advertisements are typically pushed in the form of media such as radio, television, newspaper, and the like. However, the conventional advertisement pushing method has the problems of wide advertisement coverage range, low individuation degree, difficult effect evaluation, poor user experience and the like. With the rapid development of the internet of things technology, the popularization of various devices and sensors and the popularization of the internet bring new opportunities and challenges for advertisement pushing.

The existing scheme is generally to take a two-dimensional code as a marketing entrance, organically connect all links of a marketing campaign in series and form a closed loop by means of user identification obtained by authentication and number taking, and set the two-dimensional code in the process of putting advertisements on internet of things equipment so as to find target audiences, but the existing scheme cannot effectively analyze data after the user scans the two-dimensional code, and further cannot accurately push advertisements to code scanning users. Therefore, how to realize the advertisement pushing to the user internet of things equipment by using the two-dimension code is a popular research at present.

Disclosure of Invention

The invention provides an advertisement pushing method and system based on the Internet of things, which are used for improving the advertisement pushing accuracy and efficiency of the Internet of things.

The first aspect of the invention provides an advertisement pushing method based on the Internet of things, which comprises the following steps:

acquiring first equipment position information of a plurality of fixed internet of things advertisement equipment in a target delivery area, and establishing a first equipment network topology diagram of the plurality of fixed internet of things advertisement equipment and a preset advertisement pushing platform according to the first equipment position information;

generating a first advertisement putting strategy through the advertisement putting platform, and setting a first advertisement putting model of each fixed internet of things advertisement device according to the first advertisement putting strategy and the first device network topological graph;

creating a target advertisement and a two-dimensional code corresponding to the first advertisement pushing model, carrying out two-dimensional code advertisement putting on the target advertisement and the two-dimensional code through the plurality of fixed internet of things advertisement devices, and acquiring user code scanning data and device authorization data of each fixed internet of things advertisement device;

acquiring second equipment position information corresponding to a plurality of mobile Internet of things advertising equipment associated with each fixed Internet of things advertising equipment, and performing topology analysis on the first equipment network topology graph according to the second equipment position information and the user code scanning data to obtain a second equipment network topology graph;

Constructing an advertisement push state matrix according to the second equipment network topological graph, inputting the advertisement push state matrix into a preset advertisement putting strategy optimization model, setting optimization function parameters of the advertisement putting strategy optimization model through the equipment authorization data, and generating a second advertisement putting strategy through the advertisement putting strategy optimization model;

setting a second advertisement pushing model of each mobile internet of things advertisement device according to the second advertisement putting strategy, and pushing advertisements to the plurality of mobile internet of things advertisement devices through the second advertisement pushing model.

With reference to the first aspect, in a first implementation manner of the first aspect of the present invention, the obtaining first device location information of a plurality of fixed internet of things advertisement devices in a target delivery area, and establishing a first device network topology graph of the plurality of fixed internet of things advertisement devices and a preset advertisement push platform according to the first device location information includes:

inquiring a plurality of fixed internet of things advertisement devices in a target delivery area, and acquiring first device position information of each fixed internet of things advertisement device;

establishing network connection between the plurality of fixed internet of things advertising devices and a preset advertisement pushing platform to obtain connection and transmission state parameter data;

Performing clustering calculation through the connection and transmission state parameter data to obtain a target parameter clustering result, and calculating the state priority of each fixed internet of things advertising device in the target parameter clustering result;

according to the state priority, carrying out hierarchical relation calculation on the plurality of fixed internet of things advertising devices to obtain a target hierarchical relation;

and calculating a corresponding initial equipment network topology graph through a preset minimum spanning tree algorithm according to the first equipment position information and the target hierarchical relationship, and carrying out equipment identification distribution on the initial equipment network topology graph to obtain a first equipment network topology graph.

With reference to the first aspect, in a second implementation manner of the first aspect of the present invention, the generating, by the advertisement pushing platform, a first advertisement delivery policy, and setting, according to the first advertisement delivery policy and the first device network topology map, a first advertisement pushing model of each fixed internet of things advertisement device includes:

acquiring user preference characteristic data of a target audience group in the target delivery area, and constructing an audience group portrait to the user preference characteristic data through a preset advertisement pushing platform to obtain the target audience group portrait;

Performing advertisement delivery strategy matching on the target audience group portraits through the advertisement pushing platform to obtain a first advertisement delivery strategy, wherein the first advertisement delivery strategy comprises: advertisement content, advertisement delivery time, delivery frequency and delivery position;

analyzing the connection relation and the position information of the advertising equipment on the first equipment network topological graph, and determining the distance and the coverage range between the advertising equipment;

creating a first advertisement pushing model of each fixed internet of things advertisement device according to the first advertisement putting strategy and the distance and coverage range between the advertisement devices, wherein the first advertisement pushing model comprises: the display mode, the display time length and the interaction mode of the advertisement content.

With reference to the first aspect, in a third implementation manner of the first aspect of the present invention, creating a target advertisement and a two-dimensional code corresponding to the first advertisement push model, performing two-dimensional code advertisement delivery on the target advertisement and the two-dimensional code through the plurality of fixed internet of things advertisement devices, and acquiring user code scanning data and device authorization data of each fixed internet of things advertisement device, includes:

Performing two-dimensional code conversion on the first advertisement pushing model to obtain a corresponding target advertisement and a two-dimensional code;

performing two-dimensional code advertisement delivery on the target advertisement and the two-dimensional code through the plurality of fixed internet of things advertisement devices;

the method comprises the steps of obtaining user code scanning data of each fixed internet of things advertising device through the advertisement pushing platform, wherein the user code scanning data comprise: the code scanning times and the code scanning time;

acquiring equipment authorization data of each fixed internet of things advertising equipment through the advertisement pushing platform, wherein the equipment authorization data comprises: device authorization status, authorization time, and device model.

With reference to the first aspect, in a fourth implementation manner of the first aspect of the present invention, the obtaining second device location information corresponding to a plurality of mobile internet of things advertisement devices associated with each fixed internet of things advertisement device, and performing topology analysis on the first device network topology graph according to the second device location information and the user code scanning data, to obtain a second device network topology graph includes:

acquiring a plurality of mobile internet of things advertising devices associated with each fixed internet of things advertising device according to the device authorization state in the device authorization data, and determining second device position information corresponding to each mobile internet of things advertising device;

Acquiring a plurality of first topological nodes and a plurality of first topological edges in the first equipment network topological graph, and calculating edge parameter data of each corresponding first topological edge according to the user code scanning data;

creating a plurality of second topological nodes corresponding to each first topological node according to the second equipment position information;

and carrying out topology updating on the first equipment network topology graph according to the first topology node, the second topology node and the edge parameter data to obtain a second equipment network topology graph.

With reference to the first aspect, in a fifth implementation manner of the first aspect of the present invention, the constructing an advertisement push state matrix according to the second device network topology map, inputting the advertisement push state matrix into a preset advertisement delivery policy optimization model, setting optimization function parameters of the advertisement delivery policy optimization model through the device authorization data, and generating a second advertisement delivery policy through the advertisement delivery policy optimization model includes:

performing cluster calculation on the second equipment network topological graph to obtain a target evaluation index of each topological node in the second equipment network topological graph;

Performing matrix conversion on the target evaluation index to obtain an advertisement push state matrix, and inputting the advertisement push state matrix into a preset advertisement putting strategy optimization model, wherein the advertisement putting strategy optimization model comprises two threshold circulation networks, an optimization layer and two full-connection layers;

extracting characteristic states of the advertisement push state matrix through the two-layer threshold circulation network to obtain a target characteristic state matrix;

setting optimization function parameters of an optimization layer in the advertisement putting strategy optimization model through the equipment authorization data to obtain a target optimization function, and carrying out state optimization calculation on each matrix element in the target characteristic state matrix through the target optimization function to obtain a target state optimization matrix;

optimizing and predicting the target state optimization matrix through the two full-connection layers to obtain an optimized and predicted value;

and matching the optimized predicted value with a preset advertisement putting strategy list to obtain a second advertisement putting strategy.

With reference to the first aspect, in a sixth implementation manner of the first aspect of the present invention, the setting a second advertisement pushing model of each mobile internet of things advertisement device according to the second advertisement putting policy, and pushing advertisements to the plurality of mobile internet of things advertisement devices through the second advertisement pushing model includes:

Setting a second advertisement pushing model of each mobile internet of things advertisement device according to the second advertisement putting strategy;

analyzing the second advertisement pushing model to obtain a corresponding target pushing rule, and determining an advertisement pushing list and an advertisement display sequence according to the target pushing rule;

and pushing the advertisements to the plurality of mobile Internet of things advertisement devices according to the advertisement pushing list and the advertisement display sequence.

The second aspect of the invention provides an advertisement pushing system based on the Internet of things, which comprises:

the acquisition module is used for acquiring first equipment position information of a plurality of fixed internet of things advertisement equipment in a target delivery area and establishing a first equipment network topology diagram of the plurality of fixed internet of things advertisement equipment and a preset advertisement pushing platform according to the first equipment position information;

the setting module is used for generating a first advertisement putting strategy through the advertisement putting platform and setting a first advertisement putting model of each fixed internet of things advertisement device according to the first advertisement putting strategy and the first device network topological graph;

the delivery module is used for creating a target advertisement and a two-dimensional code corresponding to the first advertisement push model, carrying out two-dimensional code advertisement delivery on the target advertisement and the two-dimensional code through the plurality of fixed internet of things advertisement devices, and acquiring user code scanning data and device authorization data of each fixed internet of things advertisement device;

The analysis module is used for acquiring second equipment position information corresponding to a plurality of mobile Internet of things advertisement equipment associated with each fixed Internet of things advertisement equipment, and carrying out topology analysis on the first equipment network topology graph according to the second equipment position information and the user code scanning data to obtain a second equipment network topology graph;

the optimizing module is used for constructing an advertisement pushing state matrix according to the second equipment network topological graph, inputting the advertisement pushing state matrix into a preset advertisement putting strategy optimizing model, setting optimizing function parameters of the advertisement putting strategy optimizing model through the equipment authorization data, and generating a second advertisement putting strategy through the advertisement putting strategy optimizing model;

and the pushing module is used for setting a second advertisement pushing model of each mobile internet of things advertisement device according to the second advertisement putting strategy, and pushing advertisements to the plurality of mobile internet of things advertisement devices through the second advertisement pushing model.

With reference to the second aspect, in a first implementation manner of the second aspect of the present invention, the acquiring module is specifically configured to:

With reference to the second aspect, in a second implementation manner of the second aspect of the present invention, the setting module is specifically configured to:

With reference to the second aspect, in a third implementation manner of the second aspect of the present invention, the delivery module is specifically configured to:

With reference to the second aspect, in a fourth implementation manner of the second aspect of the present invention, the analysis module is specifically configured to:

With reference to the second aspect, in a fifth implementation manner of the second aspect of the present invention, the optimization module is specifically configured to:

With reference to the second aspect, in a sixth implementation manner of the second aspect of the present invention, the pushing module is specifically configured to:

The third aspect of the present invention provides an advertisement pushing device based on the internet of things, comprising: a memory and at least one processor, the memory having instructions stored therein; and the at least one processor invokes the instruction in the memory to enable the advertisement pushing equipment based on the Internet of things to execute the advertisement pushing method based on the Internet of things.

A fourth aspect of the present invention provides a computer-readable storage medium having instructions stored therein, which when run on a computer, cause the computer to perform the above-described internet of things-based advertisement pushing method.

According to the technical scheme provided by the invention, a first advertisement pushing model of each fixed internet of things advertisement device is set; creating a target advertisement and a two-dimensional code, carrying out two-dimensional code advertisement putting through a plurality of fixed internet of things advertisement devices, and acquiring user code scanning data and device authorization data; acquiring a plurality of second equipment position information, and performing topology analysis according to the second equipment position information and user code scanning data to obtain a second equipment network topology map; constructing an advertisement push state matrix according to the second equipment network topological graph, inputting the advertisement push state matrix into an advertisement putting strategy optimization model, and generating a second advertisement putting strategy through the advertisement putting strategy optimization model; according to the invention, through acquiring the position information of a plurality of fixed internet of things advertisement devices in the target delivery area, a device network topology map is established, and analysis is performed according to user code scanning data and device authorization data, so that the delivery target and strategy of the advertisement can be more accurately determined. The advertisement putting strategy is generated through the preset advertisement putting platform, and the advertisement putting model is set according to the user preference characteristic data and the equipment network topological graph, so that personalized and customized advertisement contents can be provided for different users according to the user interests, the positions, the equipment relations and other factors. Through the advertisement putting strategy optimization model and the advertisement pushing state matrix, equipment authorization data and an equipment network topological graph are combined, and the advertisement putting strategy can be optimized and adjusted. By analyzing the relationship between the advertisement push status and the device, and considering the influence of the device authorization status, the effectiveness of advertisement delivery and the ROI (return on investment) can be improved. Through creating target advertisement and two-dimensional code to carry out two-dimensional code advertisement through fixed thing networking advertising equipment and put in, can guide the user initiative to sweep the code and participate in. Through establishing a network topology diagram of the second equipment, the association between the fixed internet of things advertising equipment and the mobile internet of things advertising equipment is identified, and the coverage range of advertisements can be further expanded. Advertisement pushing is carried out on mobile internet of things advertisement equipment through the advertisement pushing model and the second advertisement putting strategy, and therefore the advertisement pushing accuracy and efficiency of the internet of things are improved.

Drawings

FIG. 1 is a schematic diagram of an embodiment of an advertisement pushing method based on the Internet of things in an embodiment of the present invention;

FIG. 2 is a flowchart of setting a first advertisement push model according to an embodiment of the present invention;

FIG. 3 is a flow chart of topology analysis in an embodiment of the present invention;

FIG. 4 is a flow chart of advertisement placement strategy optimization in an embodiment of the present invention;

FIG. 5 is a schematic diagram of an embodiment of an advertisement push system based on the Internet of things according to an embodiment of the present invention;

fig. 6 is a schematic diagram of an embodiment of an advertisement pushing device based on the internet of things in an embodiment of the present invention.

Detailed Description

The embodiment of the invention provides an advertisement pushing method and system based on the Internet of things, which are used for improving the advertisement pushing accuracy and efficiency of the Internet of things. The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.

For easy understanding, the following describes a specific flow of an embodiment of the present invention, referring to fig. 1, and an embodiment of an advertisement pushing method based on internet of things in the embodiment of the present invention includes:

s101, acquiring first equipment position information of a plurality of fixed internet of things advertisement equipment in a target delivery area, and establishing a first equipment network topology diagram of the plurality of fixed internet of things advertisement equipment and a preset advertisement pushing platform according to the first equipment position information;

it can be understood that the execution subject of the present invention may be an advertisement push system based on the internet of things, and may also be a terminal or a server, which is not limited herein. The embodiment of the invention is described by taking a server as an execution main body as an example.

Specifically, the server deploys fixed internet of things advertising devices in the target delivery area and ensures that the devices can locate their own location information. The advertisement equipment of the internet of things is generally provided with a positioning module, such as GPS or Wi-Fi positioning, and the like, and the geographic position information of the equipment is obtained through the modules. The location information of the device may include longitude, latitude, altitude, and the like. And establishing network connection between a plurality of fixed internet of things advertising devices and a preset advertisement pushing platform. These devices may be connected to the advertisement push platform using internet of things communication technologies such as Wi-Fi, cellular networks (e.g., 4G, 5G), or LoRaWAN, etc. Through this connection, connection and transmission state parameter data including information of network connection states and transmission performances between devices can be acquired. And carrying out clustering calculation by using the connection and transmission state parameter data to obtain a clustering result of the target parameters. The clustering algorithm may group the devices into sets with similar features and calculate the status priority of each fixed internet of things advertising device in the clustering results. By calculating the status priority, the importance and priority of the device can be determined. And carrying out hierarchical relation calculation on the plurality of fixed internet of things advertising devices according to the state priority. And the relation of father and son or the upper and lower levels is established between the devices to form a hierarchical structure. For example, devices may be divided into a master device and a slave device according to state priorities. And according to the first equipment position information and the target hierarchical relationship, calculating to obtain an initial equipment network topological graph through a preset minimum spanning tree algorithm. The minimum spanning tree algorithm may determine the best connection between devices to form an efficient and connected network topology. Such a network topology may show the connection relationship between devices, such as the connection between a master device and a slave device. The initial device network topology is assigned device identification to ensure that each device has a unique identification in the network. This is accomplished by assigning a unique device ID or tag so that each device can be accurately identified and located during the advertisement push process. For example, assume that 10 fixed internet of things advertising devices are deployed in a commercial square, which devices are used to present advertising content to store customers. And acquiring the first equipment position information of each equipment through a GPS positioning function. The connection between these devices and the preset advertisement push platform is established over a wireless network (e.g., wi-Fi) and connection and transmission status parameter data, such as network delay, bandwidth, etc., are collected. These parameters are calculated using a clustering algorithm that divides the devices into clusters with similar connection states and transmission performance. For example, a high latency but larger bandwidth cluster and a low latency but smaller bandwidth cluster may be formed. By calculating the status priority of each device in the clustering result, it is determined which devices have higher importance in advertisement push. And according to the state priority, performing hierarchical relation calculation to divide the equipment into master equipment and slave equipment. For example, a device with a better connection state and higher performance is selected as a master device, and other devices are selected as slaves. A hierarchical relationship between devices is established. And according to the first equipment position information and the target hierarchical relationship, calculating to obtain an initial equipment network topological graph by using a minimum spanning tree algorithm. This topology may show the manner and relationship of connections between devices, such as the wiring between a master device and a slave device. The initial device network topology is assigned a device identification, and each device is assigned a unique identification, such as a device ID. In the advertisement pushing process, each device can be accurately identified and positioned, and advertisement content is put according to the position of the device in the topological graph.

S102, generating a first advertisement putting strategy through an advertisement putting platform, and setting a first advertisement putting model of each fixed internet of things advertisement device according to the first advertisement putting strategy and a first device network topological graph;

specifically, the server needs to collect user data of the target audience group in the target delivery area, including information such as interests, favorites, behavior habits and the like. These data are obtained through the user's browsing history, purchasing behavior, social media activity, etc. The user preference feature data is then analyzed and processed through a preset advertisement pushing platform to construct representations of the target audience group. Such images can help to understand the characteristics and needs of the target audience, providing basis for subsequent advertising strategies. Based on the portrait data of the target audience group, the advertisement pushing platform can utilize methods such as machine learning, data analysis and the like to match and optimize advertisement delivery strategies. This includes determining advertisement content, advertisement placement time, placement frequency, placement location, and the like. By matching the advertisement delivery strategy with the characteristics of the target audience group, the accuracy and effect of advertisement delivery can be improved. Through the first equipment network topological graph, the connection relation and the position information between the fixed internet of things advertising equipment can be known. This includes the distance and coverage between devices. This information is important for the construction of the advertisement delivery model and can determine the scope and impact of advertisement delivery. And creating a first advertisement pushing model for each fixed internet of things advertisement device based on the first advertisement putting strategy and the distance and coverage information between the advertisement devices. This model includes the manner in which the advertising content is displayed (e.g., banner advertisements, video advertisements, etc.), the duration of the advertising presentation, and the manner in which the user is interacted with (e.g., presenting a two-dimensional code for scanning by the user). By considering the advertisement putting strategy and the equipment position information, the advertisement putting effect can be optimized, and the advertisement is ensured to be optimally covered and displayed in the target putting area. For example, assuming that multiple fixed internet of things advertising devices are deployed within a shopping mall, the advertisement push platform has collected user data for shopping mall customers and built portraits of a target audience group. A first device network topology within the shopping mall displays connection relationships and location information between advertising devices. Based on representation data of the target audience group, the advertisement push platform analyzes and discovers that the customers are mainly interested in fashion, beauty and entertainment advertisements. Thus, the first advertisement delivery strategy includes playing video advertisements of make-up brands in a main channel of a shopping mall, delivering banner advertisements of entertainment activities in a restaurant area, and setting up two-dimensional code advertisements at an exit of the shopping mall that demonstrate fashion brand offers. According to the device network topology and the advertisement delivery strategy, the advertisement delivery platform creates a first advertisement delivery model for each advertisement device. For example, on a main channel advertising device, a fashion brand video advertisement is presented for 30 seconds to attract the attention of the customer. On the advertising equipment in the restaurant area, the banner advertisement is played, and the content is switched every 10 minutes, so that the customer can be ensured to notice the advertisement when eating. Meanwhile, on advertising equipment at the outlet of the shopping center, the preferential two-dimensional code is displayed for customers to scan so as to attract the customers to enter shops for shopping. Through such advertisement pushing strategy and advertisement pushing model, shopping center can carry out accurate throwing on fixed thing networking advertising equipment according to the characteristics of target audience crowd, improves the validity and the user experience of advertisement.

S103, creating a target advertisement and a two-dimensional code corresponding to the first advertisement pushing model, carrying out two-dimensional code advertisement putting on the target advertisement and the two-dimensional code through a plurality of fixed internet of things advertisement devices, and acquiring user code scanning data and device authorization data of each fixed internet of things advertisement device;

it should be noted that, the server creates a first advertisement push model according to the characteristics of the client requirement and the target audience. This model will include advertising content, advertising formats, presentation duration, interaction style, etc. In order to support two-dimensional code advertisement delivery, the server can perform two-dimensional code conversion on advertisement content to generate corresponding target advertisements and two-dimensional codes. And the server transmits the target advertisement and the two-dimension code to a plurality of fixed internet of things advertisement devices deployed in the shopping center. These advertising devices are typically connected to an advertisement push platform through internet of things technology. The server can set the time and frequency of advertisement delivery on the advertisement equipment to ensure that the advertisements are displayed to target audiences at proper time. In the advertisement putting process, each fixed internet of things advertisement device can record code scanning behavior data of a user. When a customer sees a two-dimensional code on an advertisement, some people may scan the two-dimensional code to obtain more information or participate in an activity. The code scanning data comprises code scanning times and code scanning time. The advertisement pushing platform collects the data so that the server can know the interaction effect of the advertisements, the interest degree of the users in the advertisements and the like, and therefore advertisement content and the delivery strategy are optimized. Meanwhile, the advertisement pushing platform can also acquire the equipment authorization data of each fixed internet of things advertisement equipment. These data include the authorization status of the device, the authorization time, and the device model. The device authorization state indicates whether the device is legally authorized for use, the authorization time indicates the time when the device is authorized, and the device model can help the server to know the specification and performance of the device. For example, assume that a plurality of fixed internet of things advertising devices are deployed in a shopping center, and three fixed internet of things advertising devices are located in a main channel, a food area and a home area respectively in the shopping center. The server creates a first advertisement pushing model for the shopping center and converts advertisement content into a two-dimensional code form. In the advertisement putting process, the server transmits the target advertisement and the two-dimensional code to the three advertisement devices. In the main channel, the advertisement content on the equipment is a banner advertisement of a fashion brand, and a two-dimensional code is attached to acquire coupons. In the food area, the advertisement content on the equipment is a video advertisement of food brands, and two-dimensional codes are attached to the advertisement content. In the home area, the advertisement device is put on a banner advertisement of a home brand, and the banner advertisement is also provided with a two-dimensional code to attract customers to participate in lottery activities. When customers shop in a shopping mall, they can scan the two-dimensional code on the advertisement if they are interested. The advertisement pushing platform records the user code scanning data of each advertisement device, for example, the advertisement device on the main channel records 100 code scanning behaviors, the device in the food area records 50 code scanning behaviors, and the device in the home area records 30 code scanning behaviors. These data help the server to learn how popular advertisements are and how well users interact with different areas. Meanwhile, the advertisement pushing platform also records the device authorization data of each advertisement device. The authorization states of all advertising devices are legal, authorization is obtained before cooperation of the shopping center, and the device models belong to the same specification model. By collecting and analyzing the data, the server can optimize the advertisement putting strategy, adjust the advertisement content, ensure the legal use of the advertisement equipment and improve the advertisement putting effect and the return rate.

S104, obtaining second equipment position information corresponding to a plurality of mobile Internet of things advertising equipment associated with each fixed Internet of things advertising equipment, and carrying out topology analysis on the first equipment network topology graph according to the second equipment position information and user code scanning data to obtain a second equipment network topology graph;

specifically, according to the device authorization status in the device authorization data, the advertisement pushing platform may determine a plurality of mobile internet of things advertisement devices associated with each fixed internet of things advertisement device. For an authorized mobile device, its second device location information may be obtained, for example, by GPS positioning to obtain the geographic coordinates of the device. A plurality of first topology nodes and first topology edges are obtained from a first device network topology graph. The nodes may represent fixed internet of things advertising devices while the edges represent the connection between the devices. Meanwhile, according to the code scanning data of the user, the edge parameter data of each first topological edge, such as the code scanning times or the code scanning time of the user, can be calculated. And creating a plurality of second topological nodes corresponding to each first topological node by the advertisement pushing platform according to the acquired second equipment position information. These second topological nodes may represent mobile internet of things advertising devices associated with each fixed internet of things advertising device. And carrying out topology updating on the first equipment network topology graph according to the first topology node, the second topology node and the edge parameter data. And adding a new second topological node in the network topological graph of the first equipment, and updating the corresponding connection relation according to the edge parameter data. A second device network topology map is obtained that includes connection and location information for the fixed internet of things advertising device and the associated mobile internet of things advertising device. For example, assume that a number of fixed internet of things advertising devices are deployed within a gym for showing sports branding advertisements. In addition, many gym visitors carry mobile internet of things advertising devices, such as smartwatches or smartphones. The server collects device authorization data through the advertisement push platform and determines a plurality of mobile internet of things advertisement devices associated with each fixed internet of things advertisement device. For example, during a basketball game, the server determines 100 mobile devices associated with advertising devices within a gym. The advertisement pushing platform obtains the second device position information of the mobile devices, and obtains the geographic coordinates of each mobile device through GPS positioning. Location information for each mobile device may be obtained, for example, on an audience or off-site. According to the network topology diagram of the first device, the advertisement pushing platform determines that fixed internet of things advertisement devices in the gym are used as first topology nodes and the connection relationship between the fixed internet of things advertisement devices is used as a first topology edge. By analyzing the user code scanning data, edge parameter data of each first topological edge, such as the number of times a certain advertising device is scanned, can be calculated. Based on the second device location information, the advertisement push platform creates a plurality of second topology nodes for each first topology node. For example, one fixed advertising device may be associated with location information for a plurality of mobile devices. And the advertisement pushing platform performs topology updating on the network topology graph of the first equipment according to the first topology node, the second topology node and the edge parameter data. The new second topology node is added to the first device network topology and the connection relationship is updated according to the edge parameter data. Through the process, a second equipment network topological graph is obtained, and the connection relation and the position information of the fixed internet of things advertising equipment and the associated mobile internet of things advertising equipment are displayed.

S105, constructing an advertisement push state matrix according to a second equipment network topological graph, inputting the advertisement push state matrix into a preset advertisement putting strategy optimization model, setting optimization function parameters of the advertisement putting strategy optimization model through equipment authorization data, and generating a second advertisement putting strategy through the advertisement putting strategy optimization model;

specifically, the server performs cluster calculation on the second equipment network topology graph to obtain a target evaluation index of each topology node. The clustering algorithm may group similar device nodes together, e.g., cluster according to location adjacency, device characteristics, etc., to obtain a target evaluation index for each topology node. And performing matrix conversion on the target evaluation index to obtain an advertisement push state matrix. The advertisement push state matrix is a two-dimensional matrix, wherein each row represents a topological node, and each column represents an evaluation index. The advertisement push state matrix is input into a preset advertisement putting strategy optimization model, and the model comprises two layers of threshold circulation networks, an optimization layer and two layers of full-connection layers. And extracting the characteristic state of the advertisement push state matrix through a two-layer threshold circulation network to obtain a target characteristic state matrix. The important characteristics of each topological node in the advertisement push state matrix can be extracted by utilizing the characteristics of the threshold circulation network for the subsequent optimization process. And setting optimization function parameters of an optimization layer in the advertisement putting strategy optimization model through equipment authorization data to obtain a target optimization function. The device authorization data may provide information about the device, such as authorization status, authorization time, and device model, which may be used to set parameters of the optimization function. And carrying out state optimization calculation on each matrix element in the target characteristic state matrix through a target optimization function to obtain a target state optimization matrix. And carrying out optimization prediction on the target state optimization matrix through two full-connection layers to obtain an optimization prediction value. The full connection layer can capture association and interaction between topological nodes, and accuracy of optimization prediction is further improved. And matching the optimized predicted value with a preset advertisement putting strategy list to obtain a second advertisement putting strategy. And selecting the most matched strategy as a second advertisement putting strategy by comparing the optimized predicted value with a preset advertisement putting strategy list, wherein the strategy is used for guiding the actual putting of the advertisement pushing platform to the advertisement equipment. For example, suppose a server is optimizing advertising for a shopping mall. A plurality of fixed internet of things advertising devices and mobile internet of things advertising devices are deployed in the shopping center and used for displaying advertisements of different brands to customers. The server collects device authorization data including device authorization status, authorization time and device model number through the advertisement push platform. The server performs cluster computation on advertising devices in the shopping center, and clusters together device nodes of similar characteristics and positions. For example, they cluster all stationary advertising devices located in a shopping mall home channel together, and all mobile advertising devices associated with the home channel together. The server converts the obtained target evaluation index into an advertisement push state matrix and inputs a preset advertisement putting strategy optimization model. In the optimization model, feature state extraction is carried out on the advertisement push state matrix through a two-layer threshold circulation network, and a target feature state matrix is obtained. Then, the server sets an optimization function parameter of the optimization layer according to the device authorization data, for example, sets the maximum click rate as an optimization target. And then, carrying out state optimization calculation on the target characteristic state matrix through an optimization function to obtain a target state optimization matrix. And the server continues to use the two full-connection layers to optimally predict the target state optimization matrix to obtain an optimized prediction value. And matching the optimized predicted value with a preset advertisement putting strategy list to generate a second advertisement putting strategy. For example, the server may conclude that: the click-through rate may be maximized by playing a brand of advertisements simultaneously on the main channel fixed advertising device and the associated mobile advertising device for a particular period of time in the vicinity of the main channel. And in other areas, such as home areas, different delivery strategies are adopted for different target evaluation indexes and audience groups so as to optimize advertising effects. In this way, the server can construct an advertisement push state matrix according to the second device network topology diagram, and generate a second advertisement putting strategy applicable to different areas, so that the advertisement putting optimization is realized.

S106, setting a second advertisement pushing model of each mobile internet of things advertisement device according to a second advertisement putting strategy, and pushing advertisements to a plurality of mobile internet of things advertisement devices through the second advertisement pushing model.

Specifically, according to the second advertisement delivery strategy, the server sets a corresponding second advertisement push model for each mobile internet of things advertisement device. The second advertisement push model is customized based on requirements of the second advertisement delivery strategy and characteristics of the target audience group. The server may design an appropriate advertisement push mode for each device taking into account the screen size, presentation capability, interactivity, etc. of the mobile advertising device. And analyzing the second advertisement pushing model, and analyzing the second advertisement pushing model by the server to obtain a corresponding target pushing rule. The target pushing rule comprises detail information such as advertisement content, advertisement display duration, advertisement putting time period, advertisement frequency and the like. Through the analytical model, the server can know which advertisements each advertising device should push, and what time period and frequency. And determining an advertisement push list and an advertisement display sequence according to the target push rule. The server generates a corresponding advertisement push list for each mobile internet of things advertisement device according to the target push rule, wherein the list comprises advertisement contents and display duration which need to be played on the device. Meanwhile, the server can determine the sequence of advertisement display according to rules, so that reasonable display time sequence of advertisement pushing on different devices is ensured, and the optimal advertisement putting effect is achieved. And the server pushes advertisements to the plurality of mobile Internet of things advertisement devices according to the advertisement pushing list and the advertisement display sequence. This means that the server will push the advertising content onto the corresponding mobile internet of things advertising device in a predetermined time and order. In the advertisement pushing process, the server can also monitor the playing condition of advertisements and interactive feedback of users in real time so as to optimize and adjust in real time. For example, assuming that one shopping mall needs to deliver advertisements, a plurality of mobile internet of things advertising devices are deployed inside the shopping mall, which devices are located at different floors and areas of the shopping mall, including elevator advertising screens, stair stepping advertising screens, shopping cart advertising screens, etc. And the server designs a corresponding second advertisement pushing model for each mobile internet of things advertisement device according to a second advertisement putting strategy of the shopping center. For example, on an elevator advertisement screen, the server designs a scrolling advertisement mode, each advertisement showing time is 10 seconds, and advertisements are switched every 30 seconds. On the shopping cart advertisement screen, the server designs a static advertisement display mode, each advertisement display time is 20 seconds, and advertisements are switched every 60 seconds. The server analyzes the second advertisement pushing model and obtains the corresponding target pushing rule. According to the rules, the server generates an advertisement push list and a display sequence of each mobile internet of things advertisement device. For example, on an elevator advertisement screen, the advertisement push list contains 5 different advertisement contents, and carousel is performed according to a set display duration and a switching frequency. On the shopping cart advertisement screen, the advertisement push list comprises 3 advertisement contents, and the advertisement push list is displayed according to the set display duration and the switching frequency. And then, the server pushes advertisement contents to each mobile internet of things advertisement device of the shopping center according to the set advertisement display sequence. When a customer of the shopping center takes an elevator or uses a shopping cart, the customer can see corresponding advertisement contents on the advertisement screen, so that the exposure rate and the effect of the advertisement are improved. In the advertisement pushing process, the server can monitor the playing condition of advertisements and interactive feedback of users in real time. By collecting information such as code scanning behavior data and watching time length of a user, the server can know the advertisement putting effect, so that real-time optimization and adjustment can be performed. For example, if the click-through rate of an advertisement on a particular device is low, the server may replace the advertisement content in time to increase the appeal and click-through rate of the advertisement. In this way, the server can set a second advertisement pushing model of the mobile internet of things advertisement device according to the second advertisement putting strategy, and the targeted putting and optimizing of advertisements can be realized through the pushing model.

In the embodiment of the invention, a first advertisement pushing model of each fixed internet of things advertisement device is set; creating a target advertisement and a two-dimensional code, carrying out two-dimensional code advertisement putting through a plurality of fixed internet of things advertisement devices, and acquiring user code scanning data and device authorization data; acquiring a plurality of second equipment position information, and performing topology analysis according to the second equipment position information and user code scanning data to obtain a second equipment network topology map; constructing an advertisement push state matrix according to the second equipment network topological graph, inputting the advertisement push state matrix into an advertisement putting strategy optimization model, and generating a second advertisement putting strategy through the advertisement putting strategy optimization model; according to the invention, through acquiring the position information of a plurality of fixed internet of things advertisement devices in the target delivery area, a device network topology map is established, and analysis is performed according to user code scanning data and device authorization data, so that the delivery target and strategy of the advertisement can be more accurately determined. The advertisement putting strategy is generated through the preset advertisement putting platform, and the advertisement putting model is set according to the user preference characteristic data and the equipment network topological graph, so that personalized and customized advertisement contents can be provided for different users according to the user interests, the positions, the equipment relations and other factors. Through the advertisement putting strategy optimization model and the advertisement pushing state matrix, equipment authorization data and an equipment network topological graph are combined, and the advertisement putting strategy can be optimized and adjusted. By analyzing the relationship between the advertisement push status and the device, and considering the influence of the device authorization status, the effectiveness of advertisement delivery and the ROI (return on investment) can be improved. Through creating target advertisement and two-dimensional code to carry out two-dimensional code advertisement through fixed thing networking advertising equipment and put in, can guide the user initiative to sweep the code and participate in. Through establishing a network topology diagram of the second equipment, the association between the fixed internet of things advertising equipment and the mobile internet of things advertising equipment is identified, and the coverage range of advertisements can be further expanded. Advertisement pushing is carried out on mobile internet of things advertisement equipment through the advertisement pushing model and the second advertisement putting strategy, and therefore the advertisement pushing accuracy and efficiency of the internet of things are improved.

In a specific embodiment, the process of executing step S101 may specifically include the following steps:

(1) Inquiring a plurality of fixed internet of things advertisement devices in a target delivery area, and acquiring first device position information of each fixed internet of things advertisement device;

(2) Establishing network connection between a plurality of fixed internet of things advertising devices and a preset advertisement pushing platform to obtain connection and transmission state parameter data;

(3) Clustering calculation is carried out through connection and transmission of state parameter data to obtain a target parameter clustering result, and the state priority of each fixed internet of things advertisement device in the target parameter clustering result is calculated;

(4) According to the state priority, carrying out hierarchical relation calculation on a plurality of fixed internet of things advertising devices to obtain a target hierarchical relation;

(5) According to the first equipment position information and the target hierarchical relationship, a corresponding initial equipment network topological graph is obtained through calculation of a preset minimum spanning tree algorithm, and equipment identification distribution is carried out on the initial equipment network topological graph to obtain the first equipment network topological graph.

Specifically, the server queries a plurality of fixed internet of things advertising devices in the target delivery area. This obtains the location and related information of the advertising device by communicating with a shopping mall, mall or other partner. The server establishes network connection between a plurality of fixed internet of things advertising devices and a preset advertisement pushing platform. These connections may be wireless connections, such as Wi-Fi or bluetooth, or wired connections, such as ethernet. Through the connection, the advertisement pushing platform can acquire the connection state and transmission parameter data of the advertisement equipment in real time. After the connection and transmission state parameter data are obtained, the advertisement pushing platform can perform clustering calculation on the data. The clustering algorithm may divide the advertising devices into different groups, each group having similar connection and transmission status characteristics. Through clustering, the advertisement pushing platform can obtain a target parameter clustering result. Based on the target parameter clustering result, the advertisement pushing platform can calculate the state priority of each fixed internet of things advertisement device. The status priority reflects the importance and stability of the advertising device to prioritize high priority devices during the advertisement push process. And according to the state priority, the advertisement pushing platform calculates the hierarchical relationship of the plurality of fixed internet of things advertisement devices. Through hierarchical relationship calculation, the upper and lower level relationship and the network topology structure between the advertising devices can be determined. And the advertisement pushing platform calculates and obtains a corresponding initial equipment network topological graph by using a preset minimum spanning tree algorithm according to the first equipment position information and the target hierarchical relationship. The minimum spanning tree algorithm may construct a minimum connection network containing all advertising devices such that all advertising devices in the network are capable of connectivity and the total length of the connection is minimal. After the initial device network topology diagram is obtained, the advertisement pushing platform distributes device identifiers to each device. The device identifier is a unique identifier for each device in the advertisement pushing process, and is helpful for the advertisement pushing platform to identify and manage each advertisement device. For example. And supposing that one shopping center needs to put advertisements, a plurality of fixed internet of things advertising devices are deployed in the shopping center to cover different areas such as a main channel, a stairwell, an elevator hall and the like. The server queries all advertising devices in the shopping mall and obtains first device location information for each device, such as coordinates and location area of the device. The server then establishes a network connection with all advertising devices within the shopping mall. Through these connections, the advertisement delivery platform may obtain connection status and transmission parameter data, such as network delay and data transmission rate, for each device in real time. The advertisement pushing platform performs clustering calculation on the connection and transmission state parameter data, and divides the advertisement equipment into a plurality of groups, wherein each group has similar connection characteristics. Based on the target parameter clustering result, the advertisement pushing platform calculates the state priority of each advertisement device. For example, devices may be of higher importance at the main aisle locations than devices in the stairwell, and thus the priority of the main aisle devices may be higher. And according to the state priority, the advertisement pushing platform calculates the hierarchical relationship of the advertisement equipment. For example, a main channel device may be considered a top level device, while a stairwell device may be located at a lower level. And the advertisement pushing platform calculates and obtains an initial equipment network topological graph by using a minimum spanning tree algorithm. The topology map contains all advertising devices and ensures that a minimal connected network is formed between the devices for advertisement pushing. The advertisement pushing platform distributes equipment identifiers for each equipment, so that each advertisement equipment can be accurately identified and managed in the advertisement pushing process, and the advertisement putting task is successfully completed. .

In a specific embodiment, as shown in fig. 2, the process of executing step S102 may specifically include the following steps:

s201, obtaining user preference characteristic data of a target audience group in a target delivery area, and constructing an audience group portrait to the user preference characteristic data through a preset advertisement pushing platform to obtain the target audience group portrait;

s202, carrying out advertisement delivery strategy matching on target audience group portraits through an advertisement push platform to obtain a first advertisement delivery strategy, wherein the first advertisement delivery strategy comprises the following steps: advertisement content, advertisement delivery time, delivery frequency and delivery position;

s203, analyzing the connection relation and the position information of the advertising equipment on the first equipment network topological graph, and determining the distance and the coverage range between the advertising equipment;

s204, creating a first advertisement pushing model of each fixed internet of things advertisement device according to a first advertisement putting strategy and the distance and coverage range between advertisement devices, wherein the first advertisement pushing model comprises: the display mode, the display time length and the interaction mode of the advertisement content.

Specifically, the server performs user investigation and data collection in the target delivery area. This is done in various ways, such as on-line surveys, questionnaires, user behavior analysis, etc. Through these studies and data collection, the server may obtain user preference profile data for the target audience group, such as purchasing habits, hobbies, age bracket, gender, and the like. The server transmits the collected user preference characteristic data to a preset advertisement pushing platform. And processing and analyzing the user preference characteristic data by using a machine learning algorithm and a data analysis technology on the advertisement pushing platform to construct the target audience group portraits. The target audience group portraits are descriptive information obtained by comprehensively analyzing the characteristics and behaviors of the target audience groups, and are helpful for better understanding the characteristics and requirements of the target audience groups. And carrying out advertisement putting strategy matching on the target audience group portraits through an advertisement pushing platform. According to the characteristics and the requirements of the target audience group, the advertisement pushing platform can formulate a personalized advertisement putting strategy. These strategies include selection of advertisement content, time and frequency of advertisement placement, and placement of advertisements. For example, if the target audience group is primarily young and like sports, the advertisement delivery platform may deliver relevant advertisement content in a gym or sports venue to increase the appeal and click-through rate of the advertisement. And analyzing the connection relation and the position information of the advertising equipment on the first equipment network topological graph. In the target delivery area, a plurality of fixed internet of things advertising devices are deployed by the server. By analyzing the connection relationship and the position information between the advertising devices, the distance and the coverage range between the advertising devices can be determined, and the server is helped to determine the delivery strategy and the position selection of the advertising devices. According to a first advertisement putting strategy and the distance and coverage range between advertisement devices, the advertisement pushing platform creates a first advertisement pushing model of each fixed internet of things advertisement device. The first advertisement pushing model is constructed according to the display mode, the display time length, the interaction mode and other factors of advertisement contents. Through the models, the server can display personalized advertisement contents on different advertisement devices, and the propagation effect and the user participation of advertisements are improved. For example, assuming that one shopping center needs to put advertisements, a plurality of fixed internet of things advertisement devices are deployed in different areas such as a main channel, a food area, a home area and the like of the shopping center. The server performs user investigation in the shopping center and collects user preference characteristic data of the target audience group. Through data processing and analysis, the advertisement pushing platform constructs target audience group portraits. Based on the portrayal results, the customers of the main channel area were found to be mainly young females, who were interested in fashion and beauty; customers in the food area are mainly food lovers, and like to try different food; customers in the home area are mainly housewives and pay attention to home decoration and household articles. The advertisement pushing platform formulates different advertisement delivery strategies according to the characteristics and the requirements of the target audience group. A series of fashion brand advertisements are put on the advertisement equipment in the main channel area, so that the eyes of young females are attracted. On the advertising equipment in the food area, a plurality of food advertisements are played in turn, so that customers have more choices. On the advertising equipment in the home area, advertisements of household articles are put in, and shopping requirements of housewives are met. Meanwhile, the advertisement pushing platform analyzes the distance and coverage between advertisement devices. In the main channel area, the distance between the advertising devices is relatively short, so that similar advertising content can be put in, and consistency of the advertising content is formed. The advertisement devices in different areas are far away, so that the advertisement pushing platform selects different advertisement contents to ensure the requirement of covering different target audience groups. Finally, the advertisement pushing platform creates a first advertisement pushing model of each fixed internet of things advertisement device, and displays a plurality of personalized advertisement contents in the shopping center according to different advertisement putting strategies, so that the click rate and conversion rate of advertisements are improved. Through such advertisement putting strategies, the server provides more accurate and effective advertisement service for the shopping center, and simultaneously improves the advertisement putting effect and efficiency.

In a specific embodiment, the process of executing step S103 may specifically include the following steps:

(1) Performing two-dimension code conversion on the first advertisement push model to obtain a corresponding target advertisement and a two-dimension code;

(2) Carrying out two-dimensional code advertisement delivery on the target advertisement and the two-dimensional code through a plurality of fixed internet of things advertisement devices;

(3) The method comprises the steps of obtaining user code scanning data of each fixed internet of things advertising device through an advertising push platform, wherein the user code scanning data comprise: the code scanning times and the code scanning time;

(4) Acquiring equipment authorization data of each fixed internet of things advertising device through an advertising push platform, wherein the equipment authorization data comprises: device authorization status, authorization time, and device model.

Specifically, the server processes and converts the first advertisement pushing model, converts advertisement content into target advertisements, and generates corresponding two-dimensional codes. This is done by a special two-dimensional code generation tool or programming code. The two-dimensional code is a matrix type bar code and can contain advertisement related information, such as advertisement links, product details and the like. And the server transmits the generated target advertisement and the two-dimensional code to an advertisement pushing platform deployed on a plurality of fixed internet of things advertisement devices. These advertising devices include screens, displays or projectors, etc. in various physical forms that can be used to display advertisements at different locations. The advertisement push platform is responsible for managing and controlling these advertisement devices. Through the advertisement pushing platform, the target advertisement and the two-dimension code are sent to a plurality of fixed internet of things advertisement devices, and two-dimension code advertisement putting is performed. The advertising devices display targeted advertisements and present two-dimensional codes according to predetermined time and frequency. The user can scan the two-dimensional code by using the mobile phone or other two-dimensional code scanning equipment so as to acquire more advertisement related information or participate in interactive activities. In the process of advertisement delivery, the advertisement pushing platform records user code scanning data of each fixed internet of things advertisement device. The user code scanning data comprises code scanning times and code scanning time. By collecting and analyzing this data, the server can learn about popularity of advertisements, user engagement, and evaluation of advertisement effectiveness. In addition to the user code scanning data, the advertisement pushing platform can also acquire device authorization data of each fixed internet of things advertisement device. The device authorization data includes a device authorization status, an authorization time, and a device model. Such data is important to ensure the legitimacy and stability of the advertising device. For example, assuming that one shopping mall needs to deliver advertisements, a plurality of fixed internet of things advertising devices are provided at major aisles and respective stores of the shopping mall. And the server generates a batch of target advertisements and corresponding two-dimensional codes according to the first advertisement pushing model. These targeted advertisements include promotional information, product promotions, and the like. Through the two-dimension code generation tool, the server converts advertisement content into a two-dimension code and associates the two-dimension code with the target advertisement. And then, the server transmits the target advertisement and the two-dimensional code to the advertisement pushing platform. The advertisement pushing platform distributes the advertisements to each fixed internet of things advertisement device of the shopping center, for example, the advertisements are displayed on a screen of a main channel, and a two-dimensional code is attached to the advertisement for a user to scan. When shoppers walk in a shopping mall, they notice the advertisement on the display screen and scan the two-dimensional code in the advertisement using the mobile phone. By scanning the two-dimensional code, the shopper can obtain information such as promotion offers, product details and the like. In the code scanning process, the advertisement pushing platform records the code scanning times and the code scanning time of the user. Meanwhile, the advertisement pushing platform also collects equipment authorization data of each fixed internet of things advertisement equipment, wherein the equipment authorization data comprise equipment authorization states, authorization time and equipment models. These data help the server ensure the legitimacy of the advertising device and perform device management and maintenance. By acquiring the user code scanning data and the equipment authorization data, the server can evaluate the advertisement putting effect, analyze the audience behaviors, and optimize and improve the advertisement strategy according to the data so as to improve the click rate and the conversion rate of the advertisement.

In a specific embodiment, as shown in fig. 3, the process of executing step S104 may specifically include the following steps:

s301, acquiring a plurality of mobile internet of things advertising devices associated with each fixed internet of things advertising device according to the device authorization state in the device authorization data, and determining second device position information corresponding to each mobile internet of things advertising device;

s302, acquiring a plurality of first topological nodes and a plurality of first topological edges in a first equipment network topological graph, and calculating edge parameter data of each corresponding first topological edge according to user code scanning data;

s303, creating a plurality of second topological nodes corresponding to each first topological node according to the second equipment position information;

s304, carrying out topology updating on the first equipment network topology graph according to the first topology node, the second topology node and the edge parameter data to obtain the second equipment network topology graph.

Specifically, the server obtains a plurality of mobile internet of things advertising devices associated with each fixed internet of things advertising device according to the device authorization status in the device authorization data. These mobile internet of things advertising devices may be smart phones, smart watches, or other mobile internet of things devices that carry sensors. Through the device authorization status, the server can determine which mobile devices are associated with the stationary advertising device and accurately obtain information about the relevant mobile devices. And the server determines second equipment position information corresponding to each mobile internet of things advertising equipment. This is achieved by the positioning function of the mobile device, for example by the GPS positioning system obtaining the geographical position coordinates of the device. The server may use a preset location acquisition API or communicate with the operating system of the mobile device to obtain accurate mobile device location information. Meanwhile, the server acquires a plurality of first topological nodes and a plurality of first topological edges in the first equipment network topological graph. The first topological node refers to position information of fixed internet of things advertising equipment, and the first topological edge refers to a connection relation between the fixed equipment. Through analysis of the network topology diagram of the first device, the server can know the layout and connection conditions among the advertising devices. After the information of the first topology node and the first topology edge is obtained, the server can calculate edge parameter data of each corresponding first topology edge according to the user code scanning data. These side parameter data may include information on the distance between advertising devices, transmission rate, connection stability, etc. Through calculation and analysis of the edge parameter data, the server can know communication performance between advertisement devices in the first device network topology graph. The server creates a plurality of corresponding second topological nodes for each first topological node according to the second equipment position information. The second topological node refers to the position information of the mobile internet of things advertising device. Since each fixed advertisement device is associated with a plurality of mobile devices, each first topology node corresponds to a plurality of second topology nodes, each second topology node representing location information of one mobile device. And the server performs topology updating on the first equipment network topology map by using the first topology node, the second topology node and the edge parameter data to obtain the second equipment network topology map. In the second device network topology, new connections are established between the fixed advertising device and the associated mobile device, which may be optimized based on the location and communication capabilities of the mobile device. For example, assuming that one shopping mall needs to deliver advertisements, a plurality of fixed internet of things advertising devices are provided at major aisles and respective stores of the shopping mall. The shopping mall's licensed store also has a mobile internet of things advertising device, such as a smart phone carrying a sensor. Through the device authorization data, the server is aware of the list of mobile devices associated with each of the fixed advertising devices. For example, a fixed advertising device at the primary channel is associated with a smart phone of five licensed stores. The server then obtains location information for the advertising devices, including the location of the stationary advertising devices and the location of the smart phone. The server also collects connections between the fixed advertising devices, such as which advertising devices have higher signal strength communication links between them. The server calculates edge parameter data of these connection relationships, including the distance between the advertising devices and the transmission rate. For example, the average distance between the fixed advertising device of the main channel and the smart phone of the licensed store is 10 meters, and the transmission rate is 1Mbps. Based on the second device location information, the server creates a plurality of second topology nodes for each of the fixed advertising devices, each representing location information of the mobile device associated therewith. For example, the primary channel's stationary advertising device has 5 second topology nodes, each representing the location of a smartphone at 5 licensed stores. And the server performs topology updating on the first equipment network topology graph according to the first topology node, the second topology node and the edge parameter data. By optimizing the connection, the server obtains a second device network topology map including new connections and communication capabilities between the fixed advertising device and the associated mobile device.

In a specific embodiment, as shown in fig. 4, the process of performing step S105 may specifically include the following steps:

s401, performing cluster calculation on the second equipment network topological graph to obtain a target evaluation index of each topological node in the second equipment network topological graph;

s402, performing matrix conversion on target evaluation indexes to obtain an advertisement push state matrix, and inputting the advertisement push state matrix into a preset advertisement putting strategy optimization model, wherein the advertisement putting strategy optimization model comprises a two-layer threshold circulation network, an optimization layer and two full-connection layers;

s403, extracting characteristic states of the advertisement push state matrix through a two-layer threshold circulation network to obtain a target characteristic state matrix;

s404, setting optimization function parameters of an optimization layer in an advertisement putting strategy optimization model through equipment authorization data to obtain a target optimization function, and carrying out state optimization calculation on each matrix element in a target characteristic state matrix through the target optimization function to obtain a target state optimization matrix;

s405, optimizing and predicting a target state optimization matrix through two full-connection layers to obtain an optimized prediction value;

s406, matching the optimized predicted value with a preset advertisement putting strategy list to obtain a second advertisement putting strategy.

Specifically, the server performs cluster calculation on the second device network topology graph to obtain a target evaluation index of each topology node in the second device network topology graph. The clustering calculation can classify similar equipment nodes into one type, so that the server is helped to understand the structure and the characteristics of the network topology, and a basis is provided for optimizing the follow-up advertisement delivery strategy. And the server performs matrix conversion on the target evaluation index to obtain an advertisement push state matrix. The advertisement push state matrix is a matrix with device nodes as rows and evaluation indexes as columns, wherein the evaluation index value of each device node is recorded. The advertisement push state matrix is input into a preset advertisement putting strategy optimization model, and the model comprises two layers of threshold circulation networks, an optimization layer and two layers of full-connection layers. This optimization model will help the server optimize and adjust the advertisement placement strategy. And extracting the characteristic state of the advertisement push state matrix through a two-layer threshold circulation network to obtain a target characteristic state matrix. Feature state extraction is a process of extracting useful information from a complex state matrix, which is helpful to reduce data dimensions and improve the computational efficiency of the model. And the server sets optimization function parameters of an optimization layer in the advertisement putting strategy optimization model by using the equipment authorization data to obtain a target optimization function. The optimization function is a key component in the optimization model, and the server can obtain the target state optimization matrix by carrying out state optimization calculation on each matrix element in the target characteristic state matrix. The target state optimization matrix contains optimization results for each device node that will have an impact on the formulation of the advertisement delivery strategy. And the server performs optimization prediction on the target state optimization matrix through two full-connection layers to obtain an optimization prediction value. The optimized predicted value is the prediction of the model on the optimized result of the advertisement putting strategy, and helps the server to know the optimized advertisement pushing effect. And the server matches the optimized predicted value with a preset advertisement putting strategy list to obtain a second advertisement putting strategy. The second advertisement delivery strategy is the final strategy after optimization and prediction, and comprises information such as advertisement content, advertisement delivery time, delivery frequency, delivery position and the like. Through the strategy, the server can realize accurate advertisement delivery on a plurality of fixed internet of things advertisement devices and mobile internet of things advertisement devices in the target delivery area. For example, assuming that one shopping mall needs to put advertisements, a plurality of fixed internet of things advertising devices are provided in the main aisle of the shopping mall and in different stores. Meanwhile, there are many smartphones carrying sensors in the licensed store of the shopping mall. And the server classifies the device nodes with similar characteristics into one class by carrying out cluster calculation on the second device network topological graph. For example, stationary advertising devices of a shopping mall main aisle and smart phones in licensed stores are classified as the same type, and all belong to the main aisle area. Then, the server performs matrix conversion on the target evaluation index to obtain an advertisement push state matrix. The matrix records evaluation index values of different device nodes, such as transmission rate, connection stability, etc. of the advertising device. The server inputs the advertisement push state matrix into a preset advertisement putting strategy optimization model, and the optimization model performs feature extraction on the state matrix through a two-layer threshold circulation network, and further optimizes the state matrix to obtain a target feature state matrix. Setting optimization function parameters of an optimization layer in the optimization model through equipment authorization data, and obtaining a target optimization function by a server. And then, the server performs state optimization calculation on each matrix element in the target characteristic state matrix through a target optimization function to obtain a target state optimization matrix. This matrix contains the optimization results for each device node, indicating the importance of each device node in advertising. And the server performs optimization prediction on the target state optimization matrix through two full-connection layers to obtain an optimization prediction value. And matching the predicted value with a preset advertisement putting strategy list, and obtaining a final second advertisement putting strategy by the server. The strategy will tell the server how to put advertisement content, time, frequency and location on the advertising devices in the main channel and licensed store to achieve a more accurate advertisement pushing effect.

In a specific embodiment, the process of executing step S106 may specifically include the following steps:

(1) Setting a second advertisement pushing model of each mobile internet of things advertisement device according to a second advertisement putting strategy;

(2) Analyzing the second advertisement pushing model to obtain a corresponding target pushing rule, and determining an advertisement pushing list and an advertisement display sequence according to the target pushing rule;

(3) And pushing advertisements to a plurality of mobile Internet of things advertisement devices according to the advertisement pushing list and the advertisement display sequence.

Specifically, the server sets each mobile internet of things advertisement device according to the second advertisement putting strategy. This includes determining information on advertisement content, advertisement presentation style, advertisement duration, interaction style, etc. According to different equipment characteristics and requirements of the delivery areas, the server can formulate different advertisement pushing models so as to meet personalized requirements of advertisement delivery. The server analyzes the second advertisement pushing model and extracts parameters such as advertisement content, display mode, duration and interaction mode. According to the parameters, the server can obtain corresponding target pushing rules, namely information such as advertisement content, display modes, interaction modes and the like which should be played by each device. The server divides the mobile internet of things advertising equipment into different pushing groups according to the target pushing rules, and the equipment in each group has the same advertising pushing rules. The server then determines a list of advertisement pushes, i.e., information such as advertisement content and interaction patterns that should be played by the devices within each push group. Meanwhile, the server also determines the sequence of advertisement display so as to ensure that the advertisement pushing effect is optimal. And the server pushes the advertisements to each mobile internet of things advertisement device according to the advertisement push list and the display sequence. In the process of advertisement delivery, the server can monitor the state of the equipment and feedback data of the user so as to adjust the strategy of advertisement pushing and improve the effect and accuracy of advertisement delivery. For example, assuming that one shopping mall needs to deliver advertisements, a plurality of mobile internet advertisement devices are provided in the main aisle of the shopping mall and in different shops. According to the second advertisement delivery strategy, the server determines advertisement content, display mode, duration and interaction mode of each mobile device. In the main channel of the shopping center, the device A plays video advertisements of fashion brands, an interactive two-dimensional code is set, and a user obtains coupons of the fashion brands by scanning the two-dimensional code. In a store near the equipment A, the equipment B plays advertisements of home brands, and a banner display mode is adopted, so that a user can obtain more product information by clicking a banner. The server determines the advertisement push list and the display order according to the advertisement content and the display mode of the devices. In the main channel, the device A and the device B belong to the same push group, and the advertisement content and the interaction mode of the device A and the device B are the same. The server decides to play the advertisement of device a first because the main channel is the busiest area of the shopping mall, and the advertisement of device a can attract more users' attention. Then, the advertisements of the equipment B are played in turn so as to ensure the uniformity of advertisement delivery. In the store area, devices C and D belong to another push group, and the advertising content and interaction mode they play are the same. The server decides to alternate the advertising of device C and device D to avoid the same advertising content in adjacent locations. Through the advertisement pushing strategy, the server can realize accurate advertisement putting in different areas of the shopping center, attract the attention of more users, and improve the click rate and conversion rate of advertisements. Meanwhile, the server can optimize and adjust the advertisement pushing strategy according to the feedback data of the user so as to further improve the advertisement putting effect.

The advertisement pushing method based on the internet of things in the embodiment of the present invention is described above, and the advertisement pushing system based on the internet of things in the embodiment of the present invention is described below, referring to fig. 5, an embodiment of the advertisement pushing system based on the internet of things in the embodiment of the present invention includes:

the acquisition module 501 is configured to acquire first device location information of a plurality of fixed internet of things advertisement devices in a target delivery area, and establish a first device network topology graph of the plurality of fixed internet of things advertisement devices and a preset advertisement pushing platform according to the first device location information;

the setting module 502 is configured to generate a first advertisement delivery policy through the advertisement delivery platform, and set a first advertisement delivery model of each fixed internet of things advertisement device according to the first advertisement delivery policy and the first device network topology map;

the putting module 503 is configured to create a target advertisement and a two-dimensional code corresponding to the first advertisement pushing model, perform two-dimensional code advertisement putting on the target advertisement and the two-dimensional code through the plurality of fixed internet of things advertisement devices, and acquire user code scanning data and device authorization data of each fixed internet of things advertisement device;

The analysis module 504 is configured to obtain second device location information corresponding to a plurality of mobile internet of things advertisement devices associated with each fixed internet of things advertisement device, and perform topology analysis on the first device network topology map according to the second device location information and the user code scanning data, to obtain a second device network topology map;

the optimizing module 505 is configured to construct an advertisement push state matrix according to the second device network topology graph, input the advertisement push state matrix into a preset advertisement delivery strategy optimizing model, set optimizing function parameters of the advertisement delivery strategy optimizing model through the device authorization data, and generate a second advertisement delivery strategy through the advertisement delivery strategy optimizing model;

and the pushing module 506 is configured to set a second advertisement pushing model of each mobile internet of things advertisement device according to the second advertisement putting policy, and perform advertisement pushing on the plurality of mobile internet of things advertisement devices through the second advertisement pushing model.

Optionally, the obtaining module 501 is specifically configured to:

Optionally, the setting module 502 is specifically configured to:

Optionally, the delivering module 503 is specifically configured to:

Optionally, the analysis module 504 is specifically configured to:

Optionally, the optimizing module 505 is specifically configured to:

Optionally, the pushing module 506 is specifically configured to:

Setting a first advertisement pushing model of each fixed internet of things advertisement device through the cooperative cooperation of the components; creating a target advertisement and a two-dimensional code, carrying out two-dimensional code advertisement putting through a plurality of fixed internet of things advertisement devices, and acquiring user code scanning data and device authorization data; acquiring a plurality of second equipment position information, and performing topology analysis according to the second equipment position information and user code scanning data to obtain a second equipment network topology map; constructing an advertisement push state matrix according to the second equipment network topological graph, inputting the advertisement push state matrix into an advertisement putting strategy optimization model, and generating a second advertisement putting strategy through the advertisement putting strategy optimization model; according to the invention, through acquiring the position information of a plurality of fixed internet of things advertisement devices in the target delivery area, a device network topology map is established, and analysis is performed according to user code scanning data and device authorization data, so that the delivery target and strategy of the advertisement can be more accurately determined. The advertisement putting strategy is generated through the preset advertisement putting platform, and the advertisement putting model is set according to the user preference characteristic data and the equipment network topological graph, so that personalized and customized advertisement contents can be provided for different users according to the user interests, the positions, the equipment relations and other factors. Through the advertisement putting strategy optimization model and the advertisement pushing state matrix, equipment authorization data and an equipment network topological graph are combined, and the advertisement putting strategy can be optimized and adjusted. By analyzing the relationship between the advertisement push status and the device, and considering the influence of the device authorization status, the effectiveness of advertisement delivery and the ROI (return on investment) can be improved. Through creating target advertisement and two-dimensional code to carry out two-dimensional code advertisement through fixed thing networking advertising equipment and put in, can guide the user initiative to sweep the code and participate in. Through establishing a network topology diagram of the second equipment, the association between the fixed internet of things advertising equipment and the mobile internet of things advertising equipment is identified, and the coverage range of advertisements can be further expanded. Advertisement pushing is carried out on mobile internet of things advertisement equipment through the advertisement pushing model and the second advertisement putting strategy, and therefore the advertisement pushing accuracy and efficiency of the internet of things are improved.

Fig. 5 above describes the advertisement pushing system based on the internet of things in the embodiment of the present invention in detail from the perspective of a modularized functional entity, and the advertisement pushing device based on the internet of things in the embodiment of the present invention is described in detail from the perspective of hardware processing below.

Fig. 6 is a schematic structural diagram of an advertisement pushing device based on the internet of things, where the advertisement pushing device 600 based on the internet of things may generate relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 610 (e.g., one or more processors) and a memory 620, and one or more storage media 630 (e.g., one or more mass storage devices) storing application programs 633 or data 632. Wherein the memory 620 and the storage medium 630 may be transitory or persistent storage. The program stored on the storage medium 630 may include one or more modules (not shown), each of which may include a series of instruction operations on the internet of things-based advertisement pushing device 600. Still further, the processor 610 may be configured to communicate with the storage medium 630 and execute a series of instruction operations in the storage medium 630 on the internet of things-based advertisement pushing device 600.

The internet of things-based advertisement pushing device 600 may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input/output interfaces 660, and/or one or more operating systems 631, such as Windows Server, mac OS X, unix, linux, freeBSD, and the like. It will be appreciated by those skilled in the art that the internet of things-based advertisement pushing device structure shown in fig. 6 does not constitute a limitation of the internet of things-based advertisement pushing device, and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.

The invention also provides the advertisement pushing equipment based on the Internet of things, which comprises a memory and a processor, wherein the memory stores computer readable instructions, and when the computer readable instructions are executed by the processor, the processor executes the steps of the advertisement pushing method based on the Internet of things in the above embodiments.

The invention also provides a computer readable storage medium, which can be a nonvolatile computer readable storage medium, and can also be a volatile computer readable storage medium, wherein the computer readable storage medium stores instructions, and when the instructions run on a computer, the instructions cause the computer to execute the steps of the advertisement pushing method based on the internet of things.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. The advertisement pushing method based on the Internet of things is characterized by comprising the following steps of:

Acquiring second equipment position information corresponding to a plurality of mobile Internet of things advertising equipment associated with each fixed Internet of things advertising equipment, and performing topology analysis on the first equipment network topology graph according to the second equipment position information and the user code scanning data to obtain a second equipment network topology graph; the method specifically comprises the following steps: acquiring a plurality of mobile internet of things advertising devices associated with each fixed internet of things advertising device according to the device authorization state in the device authorization data, and determining second device position information corresponding to each mobile internet of things advertising device; acquiring a plurality of first topological nodes and a plurality of first topological edges in the first equipment network topological graph, and calculating edge parameter data of each corresponding first topological edge according to the user code scanning data; creating a plurality of second topological nodes corresponding to each first topological node according to the second equipment position information; performing topology updating on the first equipment network topology graph according to the first topology node, the second topology node and the edge parameter data to obtain a second equipment network topology graph;

constructing an advertisement push state matrix according to the second equipment network topological graph, inputting the advertisement push state matrix into a preset advertisement putting strategy optimization model, setting optimization function parameters of the advertisement putting strategy optimization model through the equipment authorization data, and generating a second advertisement putting strategy through the advertisement putting strategy optimization model; the method specifically comprises the following steps: performing cluster calculation on the second equipment network topological graph to obtain a target evaluation index of each topological node in the second equipment network topological graph; performing matrix conversion on the target evaluation index to obtain an advertisement push state matrix, and inputting the advertisement push state matrix into a preset advertisement putting strategy optimization model, wherein the advertisement putting strategy optimization model comprises two threshold circulation networks, an optimization layer and two full-connection layers; extracting characteristic states of the advertisement push state matrix through the two-layer threshold circulation network to obtain a target characteristic state matrix; setting optimization function parameters of an optimization layer in the advertisement putting strategy optimization model through the equipment authorization data to obtain a target optimization function, and carrying out state optimization calculation on each matrix element in the target characteristic state matrix through the target optimization function to obtain a target state optimization matrix; optimizing and predicting the target state optimization matrix through the two full-connection layers to obtain an optimized and predicted value; matching the optimized predicted value with a preset advertisement putting strategy list to obtain a second advertisement putting strategy;

2. The method for pushing advertisement based on internet of things according to claim 1, wherein the obtaining the first device location information of the plurality of fixed internet of things advertisement devices in the target delivery area, and establishing a first device network topology diagram of the plurality of fixed internet of things advertisement devices and a preset advertisement pushing platform according to the first device location information, comprises:

3. The internet of things-based advertisement pushing method according to claim 1, wherein the generating, by the advertisement pushing platform, a first advertisement delivery policy, and setting a first advertisement pushing model of each fixed internet of things advertisement device according to the first advertisement delivery policy and the first device network topology map, includes:

4. The internet of things-based advertisement pushing method according to claim 1, wherein the creating the target advertisement and the two-dimensional code corresponding to the first advertisement pushing model, performing two-dimensional code advertisement delivery on the target advertisement and the two-dimensional code through the plurality of fixed internet of things advertisement devices, and acquiring the user scan code data and the device authorization data of each fixed internet of things advertisement device, includes:

5. The internet of things-based advertisement pushing method according to claim 1, wherein the setting a second advertisement pushing model of each mobile internet of things advertisement device according to the second advertisement putting policy, and pushing advertisements to the plurality of mobile internet of things advertisement devices through the second advertisement pushing model, comprises:

6. An advertisement pushing system based on the internet of things, which is characterized by comprising:

the analysis module is used for acquiring second equipment position information corresponding to a plurality of mobile Internet of things advertisement equipment associated with each fixed Internet of things advertisement equipment, and carrying out topology analysis on the first equipment network topology graph according to the second equipment position information and the user code scanning data to obtain a second equipment network topology graph; the method specifically comprises the following steps: acquiring a plurality of mobile internet of things advertising devices associated with each fixed internet of things advertising device according to the device authorization state in the device authorization data, and determining second device position information corresponding to each mobile internet of things advertising device; acquiring a plurality of first topological nodes and a plurality of first topological edges in the first equipment network topological graph, and calculating edge parameter data of each corresponding first topological edge according to the user code scanning data; creating a plurality of second topological nodes corresponding to each first topological node according to the second equipment position information; performing topology updating on the first equipment network topology graph according to the first topology node, the second topology node and the edge parameter data to obtain a second equipment network topology graph;

The optimizing module is used for constructing an advertisement pushing state matrix according to the second equipment network topological graph, inputting the advertisement pushing state matrix into a preset advertisement putting strategy optimizing model, setting optimizing function parameters of the advertisement putting strategy optimizing model through the equipment authorization data, and generating a second advertisement putting strategy through the advertisement putting strategy optimizing model; the method specifically comprises the following steps: performing cluster calculation on the second equipment network topological graph to obtain a target evaluation index of each topological node in the second equipment network topological graph; performing matrix conversion on the target evaluation index to obtain an advertisement push state matrix, and inputting the advertisement push state matrix into a preset advertisement putting strategy optimization model, wherein the advertisement putting strategy optimization model comprises two threshold circulation networks, an optimization layer and two full-connection layers; extracting characteristic states of the advertisement push state matrix through the two-layer threshold circulation network to obtain a target characteristic state matrix; setting optimization function parameters of an optimization layer in the advertisement putting strategy optimization model through the equipment authorization data to obtain a target optimization function, and carrying out state optimization calculation on each matrix element in the target characteristic state matrix through the target optimization function to obtain a target state optimization matrix; optimizing and predicting the target state optimization matrix through the two full-connection layers to obtain an optimized and predicted value; matching the optimized predicted value with a preset advertisement putting strategy list to obtain a second advertisement putting strategy;

7. Advertisement pushing equipment based on thing networking, its characterized in that, advertisement pushing equipment based on thing networking includes: a memory and at least one processor, the memory having instructions stored therein;

the at least one processor invokes the instructions in the memory to cause the internet of things based advertisement pushing device to perform the internet of things based advertisement pushing method of any of claims 1-5.

8. A computer readable storage medium having instructions stored thereon, which when executed by a processor, implement the internet of things based advertisement pushing method of any of claims 1-5.