WO2019061663A1

WO2019061663A1 - Method for optimizing wi-fi hotspot deployment, server and storage medium

Info

Publication number: WO2019061663A1
Application number: PCT/CN2017/108771
Authority: WO
Inventors: 金新; 王建明; 肖京
Original assignee: 平安科技（深圳）有限公司
Priority date: 2017-09-26
Filing date: 2017-10-31
Publication date: 2019-04-04
Also published as: CN107809740A; CN107809740B

Abstract

Provided in the present application is a method for optimizing Wi-Fi hotspot deployment, the method comprising: acquiring positioning information of a first mobile terminal as well as a scanned Wi-Fi hotspot list, the positioning information comprising the latitude and longitude of the first mobile terminal; aggregating Wi-Fi hotspot lists within multiple business districts; determining a centralized area of Wi-Fi hotspots within the multiple business districts; calculating the user satisfaction of a first user for a Wi-Fi hotspot within the multiple business districts; screening out a second business district in response to an operation of a second user selecting a first business district, and, according to the number of Wi-Fi hotspots and the number of first users within the second business district as well as a centralized area of human traffic and a centralized area of Wi-Fi hotspots in the first business district, determining the number and locations of Wi-Fi hotspots requiring adjustment to improve user satisfaction in the first business district. Further provided in the present application are a server and a computer-readable storage medium. The present application provides a solution for optimizing Wi-Fi hotspot deployment within a business district by using the distribution of Wi-Fi hotspot in the business district as well as user satisfaction so as to improve the user experience in going online.

Description

Wi-Fi hotspot deployment optimization method, server and storage medium

Priority claim

The present application is based on the priority of the Chinese Patent Application entitled "Wi-Fi Hotspot Deployment Optimization Method, Server and Storage Medium" filed on September 26, 2017, with the application number of CN201710883895.1, which is filed on September 26, 2017. The overall content is incorporated herein by reference.

Technical field

The present application relates to the field of computer technologies, and in particular, to a Wi-Fi hotspot deployment optimization method, a server, and a computer readable storage medium.

Background technique

With the development of technology and the advancement of society, wireless Wi-Fi (Wireless-Fidelity) technology is very important in people's lives, but due to the randomness of the distribution of wireless signal hotspots, the lack of location for hot spots is reasonable. The characteristics of control and restraint, blindness and randomness are very obvious. Consumer electronics products such as mobile phones, game consoles, and portable computers are becoming more and more popular. The richness of terminal products will make the penetration rate of Wi-Fi higher and higher. It is of substantial significance to strengthen the coverage of Wi-Fi signals.

At present, the person in the field determines whether the current location of the to-be-arranged space exists by calculating the coverage area of the hot spot, and if so, adjusts the location of the hot spot toward the blind spot outside the coverage area of the hot spot, or at a position close to the blind spot. A hot spot is arranged until the entire location of the space to be laid is covered by at least one hot spot, thereby optimizing the arrangement of the Wi-Fi hotspot.

However, for a business district where Wi-Fi hotspot deployment needs to be optimized, it is necessary to consider the traffic volume in the business circle and the user satisfaction with the Wi-Fi hotspot in the business circle, so as to be based on user satisfaction and within the business circle. The traffic aggregation area determines what problems exist in the deployment of existing Wi-Fi hotspots. Therefore, how to make full use of Wi-Fi hotspots, adjust the location of existing Wi-Fi hotspot deployments, and increase the signal coverage of Wi-Fi hotspots. The crowd, improving the user's online experience, is an urgent problem to be solved.

Summary of the invention

The present application provides a Wi-Fi hotspot deployment optimization method, a server, and a computer readable storage medium, the main purpose of which is to understand the user's satisfaction with the Wi-Fi hotspot in the business circle and the distribution of Wi-Fi hotspots in the business circle. An optimization scheme for Wi-Fi hotspot deployment in the business circle is given to enhance the user experience of Wi-Fi hotspots.

To achieve the above objective, the present application provides a server, including: a memory, a processor, and a Wi-Fi hotspot deployment optimization program stored on the memory, where the optimization program is executed by the processor to implement the following steps:

The collecting step: collecting the positioning information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location, where the positioning information includes the current location of the first mobile terminal Latitude and longitude;

a first calculating step: calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the first preset level of the hash value, and scanning the first mobile terminal at the current location according to the result of the first preset level The list of Wi-Fi hotspots is aggregated in multiple business districts;

a second calculating step: calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the second preset level of the hash value, and determining, according to the result of the second preset level, the Wi- in the plurality of shopping districts a concentrated area of Fi hotspots;

a third calculating step: reading historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculating, by the first user of the first mobile terminal, the Wi-Fi hotspot in the multiple shopping districts User satisfaction; and

An optimization step of: selecting, in the second mobile terminal, a click operation of selecting a first business circle from the plurality of shopping circles, and screening a second business circle from the plurality of business circles, the second business The number of first users in the plurality of business circles is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the number of first users Correlation relationship, determine the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle. According to the traffic flow aggregation area and the Wi-Fi hotspot concentration area in the first business circle, it is determined that the user satisfaction of the first business circle needs to be adjusted. The location of the Wi-Fi hotspot.

In addition, to achieve the above object, the present application further provides a Wi-Fi hotspot deployment optimization method, where the method includes:

The acquiring step: collecting the positioning information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal;

An optimization step of: selecting, in the second mobile terminal, a click operation of selecting a first business circle from the plurality of shopping circles, and screening a second business circle from the plurality of business circles, the second business The number of first users in the plurality of business circles is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the number of first users Correlation relationship, determine the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle. According to the traffic flow aggregation area and the Wi-Fi hotspot concentration area in the first business circle, it is determined that the user satisfaction of the first business circle needs to be adjusted. of The location of the Wi-Fi hotspot.

In addition, in order to achieve the above object, the present application further provides a computer readable storage medium, where the Wi-Fi hotspot deployment optimization program is stored, and the optimized program is executed by the processor to implement the foregoing Steps to deploy an optimization method for Wi-Fi hotspots.

Compared with the prior art, the method, the server, and the computer readable storage medium provided by the present application calculate the user's satisfaction with the Wi-Fi hotspots of each business circle by acquiring historical data of all Wi-Fi hotspots scanned by the mobile terminal. According to the calculation result, the optimization scheme of Wi-Fi hotspot deployment in the business circle with lower user satisfaction is given according to the calculation result, and the Wi-Fi hotspot coverage population is increased, and the user's Internet access is increased. Experience.

DRAWINGS

1 is a schematic diagram of a preferred embodiment of a server of the present application;

2 is a schematic block diagram of a preferred embodiment of the Wi-Fi hotspot deployment optimization program of FIG. 1;

FIG. 3 is a flowchart of a preferred embodiment of a Wi-Fi hotspot deployment optimization method according to the present application.

The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings.

Detailed ways

It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting.

The application provides a server 1. Referring to FIG. 1, a schematic diagram of a preferred embodiment of the server 1 of the present application is shown. In the present embodiment, the server 1 includes a memory 11, a processor 12, a network interface 13, and a communication bus 14. Among them, the communication bus 14 is used to implement connection communication between these components.

Server 1 can be a rack server, a blade server, a tower server, or a rack server.

The network interface 13 may include a standard wired interface, a wireless interface (such as a WI-FI interface). Usually used to connect to mobile terminals. In this embodiment, the server 1 connects the plurality of first mobile terminals 21 and the second mobile terminal 22 through the network interface 13. The first mobile terminal 21 and the second mobile terminal 22 may be terminal devices having a wireless local area network configuration and display function, such as a notebook, a tablet, a smart phone, and an e-book reader.

The memory 11 includes at least one type of readable storage medium. The at least one type of readable storage medium may be a non-volatile storage medium such as a flash memory, a hard disk, a multimedia card, a card type memory, or the like. In some embodiments, the readable storage medium may be an internal storage unit of the server 1, such as a hard disk of the server 1. In other embodiments, the readable storage medium may also be an external storage device of the server 1, such as a plug-in hard disk equipped on the server 1, a smart memory card (SMC), and security. Digital (Secure Digital, SD) card, flash card (Flash Card), etc.

In this embodiment, the readable storage medium of the memory 11 is generally used to store a Wi-Fi hotspot deployment optimization program installed in the server 1, a Wi-Fi hotspot collected by the first mobile terminal 21, and historical data of the user. Model files of pre-determined and updated logistic regression models, distribution of human traffic within each business district obtained from third parties, etc. The memory 11 can also be used to temporarily store data that has been output or is about to be output.

The processor 12, in some embodiments, may be a Central Processing Unit (CPU), microprocessor or other data processing chip for running program code or processing data stored in the memory 11, such as performing Wi-Fi. Hotspot deployment optimizer, etc.

Figure 1 shows only server 1 with components 11-14 and Wi-Fi hotspot deployment optimizer 10, but it should be understood that not all illustrated components may be implemented, alternative implementations may be more or less Component.

Optionally, the server 1 may further include a user interface, and the user interface may include an input unit such as a keyboard, and the optional user interface may further include a standard wired interface and a wireless interface.

Optionally, the server 1 may further include a display, which may also be referred to as a display screen or a display unit. In some embodiments, it may be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch sensor, or the like. The display is used to display information processed in the server 1 and a user interface for displaying visualizations.

Optionally, the server 1 may further include a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, and the like, and details are not described herein.

In the embodiment shown in FIG. 1, a Wi-Fi hotspot deployment optimizer 10 is stored in the memory 11, and the processor 12 performs the following steps when executing the Wi-Fi hotspot deployment optimization program 10 stored in the memory 11:

The acquiring step: collecting the positioning information of the first mobile terminal 21 at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal 21 at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal 21;

a first calculating step: calculating a hash value of the latitude and longitude of the current location of the first mobile terminal 21, taking a result of the first preset level of the hash value, and using the first preset level as a result of the first preset level The list of Wi-Fi hotspots scanned by the location is aggregated in multiple business districts;

a second calculating step: calculating a latitude and longitude hash value of the current position of the first mobile terminal 21, taking a result of the second preset level of the hash value, and determining, according to the result of the second preset level, the Wi in the plurality of business circles - the concentrated area of the Fi hotspot;

a third calculating step: reading historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculating, by the first user of the first mobile terminal 21, Wi-Fi in the multiple shopping districts Hot user satisfaction; and

An optimization step of: selecting, in the second mobile terminal 22, a click operation of selecting a first business circle from the plurality of shopping circles, selecting a second business circle from the plurality of business circles, the second The number of first users in the plurality of business districts is equal to the number of first users in the first business circle and the user is satisfied The highest degree, according to the relationship between the number of Wi-Fi hotspots in the second business circle and the number of first users, determine the number of Wi-Fi hotspots that need to be adjusted to improve the satisfaction of the first business circle, according to the first business circle The traffic aggregation area and the Wi-Fi hotspot concentration area determine the location of the Wi-Fi hotspot that needs to be adjusted to improve the user satisfaction of the first business circle.

In this embodiment, each city has a plurality of different business districts, wherein the business circle refers to a certain range of areas, and the first user refers to accessing and using the Wi-Fi hotspots in each business circle through the first mobile terminal 21. User, the second user refers to the staff of the Wi-Fi hotspot provider, and the second user knows the distribution of Wi-Fi hotspots in each business circle through the second mobile terminal 22 and the first user to Wi-Fi in each business circle The user satisfaction of the hotspot is that the first mobile terminal 21 is installed with an APP for connecting to the Wi-Fi hotspot, and the APP can obtain location information (latitude and longitude) of the first mobile terminal 21 at the current location, and the second mobile terminal 22 is installed with Wi-Fi hotspot deployment optimizer 10 client program. Hotspot vendors can use a variety of channels to understand the areas where the first users of each city's business districts gather, such as obtaining relevant data through third parties.

When it is required to optimize the deployment of the Wi-Fi hotspot in a certain business circle, the APP scans the Wi-Fi hotspot list available at the current location through the first mobile terminal 21, and collects all Wi-Fi hotspots in the Wi-Fi hotspot list. Historical data within a preset time (one week), including: Wi-Fi name, time of access, time of operation, operational status (connection success, connection failure, login success, login failure, etc.), frequency of access, availability by operator Etc. Then, the above historical data is sent to the server 1. The server 1 extracts key historical data, such as Wi-Fi identification, time, location, connection operation, Internet access duration, number of successful connections, and number of connection failures, through the data collection technology (Extract-Transform-Load, ETL). The number of retries, the number of successful logins, the number of failed logins, and the like are saved in the memory 11 for subsequent user satisfaction calculation operations.

It can be understood that when the first mobile terminal 21 scans the available Wi-Fi hotspot list at a certain location, the transmitting device of the Wi-Fi hotspot in the Wi-Fi hotspot list (hereinafter referred to as Wi-Fi hotspot) is also Located near the location of the first mobile terminal 21, the location of the Wi-Fi hotspot can be estimated based on the location information of the first mobile terminal 21. It should be understood that the geohash algorithm can be used to calculate the latitude and longitude hash values, and the hash values of different levels can be different. For example, one to nine results can be taken, and the six-level result is expressed as a range of 1.2 km*1.2 km. (Approximately can be understood as the scope of a business circle), taking a seven-level result indicating a range of 152m * 152m.

Taking the first mobile terminals A, B, C, D, and E as an example, the Wi-Fi hotspot lists scanned by the first mobile terminal at the current location are a, b, c, d, and e, respectively, assuming a first preset. The level is six, the server 1 reads the latitude and longitude of the current position of the first mobile terminal A, B, C, D, E from the memory 11, performs a geohash operation, and calculates the latitude and longitude hash value of the current position of each first mobile terminal 21. If the six-level hash value of the first mobile terminal A, B, C, D, and E is the same, it is determined that the first mobile terminal A, B, C, D, and E are in the same business circle. Correspondingly, the Wi-Fi hotspots in the Wi-Fi lists a, b, c, d, and e are also located in the business circle.

After the pre-determination of the Wi-Fi hotspot in the business circle, the second calculation step is needed to determine the area of the Wi-Fi hotspot in the business circle. Specifically, the second calculating step includes: according to the second preset The result of the level, the Wi-Fi hotspot list in each business circle is divided into different regional blocks smaller than the business circle; in the Wi-Fi hotspot list in the different regional blocks, the Wi with the same Wi-Fi hotspot will be The -Fi hotspot list is merged to form a new Wi-Fi hotspot list; the different regional blocks in which the Wi-Fi hotspot list with the same Wi-Fi hotspot is located are merged to form a new regional block, and Wi-Fi in different new regional blocks is determined. The number of hotspots; and, based on the number of Wi-Fi hotspots in the new block of the business district, the area where Wi-Fi hotspots are concentrated in each business district.

Assume that the second preset level is seven levels, performing a geohash operation on the latitude and longitude of the current location of the first mobile terminal A, B, C, D, and E, and taking a seven-level result of the hash value, wherein the first mobile terminal A, C The seven-level result is the same, the seventh-level results of the first mobile terminal B, E are the same, and the multiple Wi-Fi hotspots in the Wi-Fi hotspot list a, c are divided into the regional block P, and the Wi-Fi hotspot list b is The plurality of Wi-Fi hotspots in the e are divided into the area block Q, and the plurality of Wi-Fi hotspots in the Wi-Fi hotspot list d are separately divided into the area block O. If there are duplicate Wi-Fi hotspots in the Wi-Fi hotspot list in the same area block, deduplication is performed on the Wi-Fi hotspots in each of the two Wi-Fi hotspot lists, and the two Wis after deduplication are performed. -Fi hotspot list merges into one Wi-Fi hotspot list until there is no duplicate Wi-Fi hotspot between each Wi-Fi hotspot list in the same block, that is, if there is originally 20 in a certain block A list of Wi-Fi hotspots, after deduplication, the number of Wi-Fi hotspot lists will be less than or equal to 20.

It can be understood that, assuming that the transmitting device of a Wi-Fi hotspot is located between two points, and both points are within the coverage of the Wi-Fi hotspot, then different first mobile terminals located between the two points 21 can scan the Wi-Fi hotspot, that is, according to different latitude and longitude in the positioning information of the first mobile terminal 21, the same Wi-Fi hotspot may be divided into the middle lines of two adjacent different regional blocks. There is a nearby Wi-Fi hotspot, so this type of Wi-Fi hotspot needs to be further processed. Assuming that the area blocks P and Q are adjacent, and the same Wi-Fi hotspot exists in the Wi-Fi hotspot list in the area blocks P and Q, then the area blocks P and Q are merged into a new area block, and De-duxing the Wi-Fi hotspots in all Wi-Fi hotspot lists in this new block, maximizing the number of Wi-Fi hotspots in the new block; then, in multiple new blocks The Wi-Fi hotspots are merged and de-duplicated until there are no duplicate Wi-Fi hotspots in all the blocks in the business circle and in the block. There are many cases, and the number of new blocks is relatively small. The range of new blocks is different. The number of Wi-Fi hotspots in each new block is different. Some of the new blocks have a large number of Wi-Fi hotspots, and some have few Wi-Fi. The obtained distribution of each block and the number of Wi-Fi hotspots in each block are linked to the electronic map of the business circle, so that the area where the Wi-Fi hotspot is concentrated in the business circle can be determined.

Next, reading key historical data of the Wi-Fi hotspot in each business circle within a preset time (for example, one week), and calculating the first user's user satisfaction with the Wi-Fi hotspot in each business circle, specifically, according to The historical data of the past week, calculate the user indicators of the Wi-Fi hotspots in each business circle, and weight the aggregated user satisfaction of the first user. The calculation formula is:

S=C*L*T ₁ /(T ₂ ^1/9 )

Among them, S is the first user's satisfaction with the Wi-Fi hotspots in each business circle, C is the average connection success rate of Wi-Fi hotspots in each business circle, and L is the average landing of Wi-Fi hotspots in each business circle. Success rate, T ₁ is the average online time (in min) of Wi-Fi hotspots in each business circle, and T ₂ is the average connection of Wi-Fi hotspots in each business circle to power consumption (in s). In order to make the calculation more accurate, the abnormal values (such as the maximum value and the minimum value) need to be removed when calculating C, L, T ₁ and T ₂ , and the actual network time length is rounded when calculating T ₁ , and the value is 20 minutes over 10 minutes. Take 10 minutes for less than 10 minutes.

In other embodiments, the third calculating step includes: calculating, according to historical data of the Wi-Fi hotspot in each business circle within a preset time period and a predetermined logistic regression model, the first user to Wi- in each business circle. User satisfaction of Fi hotspots.

The Wi-Fi operator may collect a first user's user satisfaction sample for the Wi-Fi hotspot in the business circle through an operation questionnaire or a user scoring system, and the predetermined logistic regression model is used to calculate the first user to each business circle. User satisfaction of the internal Wi-Fi hotspot, the model file of the logistic regression model is stored in the memory 11, which can collect the user satisfaction sample and the key historical data of the Wi-Fi hotspot in the business circle in the past three months. Offline training is available.

It should be noted that the advantage of the offline training model is that it utilizes a large amount of historical data, and the sample is sufficient. The advantage of the online training model is that it can use the latest data, the model can adapt to the changes of real-time data, and the online model is more accurate in the case of large data distribution and historical gap. In order to make the user satisfaction of the Wi-Fi hotspots in each commercial circle obtained in the subsequent calculation more accurate, the above-mentioned logistic regression model can be updated every three days. Then, the key historical data of the Wi-Fi hotspot in each business circle in the latest week is read from the memory 11, and the updated logistic regression model is input, and the user satisfaction of the first user to the Wi-Fi hotspot in the business circle is calculated. By combining offline training and online training, the advantages of both can be taken to improve the accuracy of the model, and at the same time, the problem of too little data volume or real-time model update failure caused by network and system problems is prevented in the online environment. There is already a mature calculation method for training and updating the model and using it to calculate the user satisfaction of Wi-Fi hotspots in each business circle, and will not be described here.

Further, an electronic map is installed on the second mobile terminal 22, and a map of all cities is displayed to the second user through the electronic map, and when the second user selects a certain city, the location and the merchants of all the business districts of the city are also displayed. User satisfaction in Wi-Fi hotspots in the circle. When a Wi-Fi hotspot provider needs to optimize the deployment of a Wi-Fi hotspot in a certain business circle to improve the user satisfaction of the Wi-Fi hotspot in the business circle, the business circle is selected, and the server 1 will respond to the click operation. Taking the business circle B as an example, the number of the first user is currently a, and the server 1 filters out the user from the number of the first user and the current number of the first user of the business circle B (for example, a±50). The highest satisfaction business circle G, according to the relationship between the number of Wi-Fi hotspots in the business circle G and the number of first users, determine whether the Wi-Fi hotspot should be increased or decreased in the business circle B, and then aggregate according to the traffic flow in the business circle B. The area is compared with the concentrated area of the Wi-Fi hotspot in the business circle B, and it is determined that the location of the Wi-Fi hotspot needs to be adjusted in the business circle B.

Specifically, if the number of Wi-Fi hotspots in the business circle G (for example, m) is significantly more than the number of Wi-Fi hotspots in the business circle B (for example, n), then the corresponding number (mn) needs to be added in the business circle B. The Wi-Fi hotspot is equal to the number of Wi-Fi hotspots in the business district G; if the number of Wi-Fi hotspots in the business circle G is less than B or equivalent, the number of Wi-Fi hotspots does not cause the business circle B, G user The main reason for the difference in satisfaction is to further consider whether the location of the Wi-Fi hotspot is reasonable.

It can be understood that for the area where the traffic volume in the business circle is concentrated, the demand for the Wi-Fi hotspot is also relatively large. Then, after reading the distribution area of the traffic flow in the business circle B obtained from the third party from the memory 11 The comparison between the traffic aggregation area in the business circle B and the centralized area of the Wi-Fi hotspot in the business circle B obtained through the second calculation step is the same. If the centralized area of the first user aggregation area and the Wi-Fi hotspot is inconsistent, the business is The first user aggregation area of circle B has fewer Wi-Fi hotspots, and there are more Wi-Fi hotspots in the area where there are fewer first users, so it is necessary to adjust some Wi-Fi hotspots from the area where the first user is less to the first user. In the aggregation area, if the first user aggregation area and the centralized area of the Wi-Fi hotspot are the same, the quality problem may exist in the Wi-Fi hotspot in the business circle B. It is recommended to replace the Wi-Fi hotspot.

Finally, the server 1 displays the distribution of the Wi-Fi hotspots in the shopping circle to the second user through the first display area of the second mobile terminal 22, and displays the improvement in the business circle B in the second display area of the second mobile terminal 22. Wi-Fi hotspot user satisfaction Wi-Fi hotspot adjustment program.

It should be noted that for different business circles, it needs to be treated differently, such as shopping centers, schools, office buildings, suburbs, etc. The solution of this application is applicable to shopping centers, but it is not necessarily applicable to schools or other areas. In the case of remote suburbs, due to local restrictions, regardless of the number of Wi-Fi added, or the replacement of Wi-Fi, the Wi-Fi hotspots are improved. Satisfaction scores do not contribute significantly.

The server 1 proposed in the above embodiment calculates the user's satisfaction with the Wi-Fi hotspots of each business circle and the Wi-Fi hotspots in each business circle by acquiring the historical data of all the Wi-Fi hotspots scanned by the first mobile terminal 21. In the aggregation area, according to the calculation result, an optimization scheme for Wi-Fi hotspot deployment in the business circle with lower user satisfaction is given, and the Wi-Fi hotspot coverage population is increased to improve the user's online experience.

Alternatively, in other embodiments, the Wi-Fi hotspot deployment optimizer 10 may also be partitioned into one or more modules, one or more modules being stored in the memory 11 and being processed by one or more processors 12 implementations to complete this application. A module as referred to in this application refers to a series of computer program instructions that are capable of performing a particular function. Referring to FIG. 2, it is a block diagram of a preferred embodiment of the Wi-Fi hotspot deployment optimization program 10 of FIG.

The Wi-Fi hotspot deployment optimization program 10 can be divided into: an acquisition module 110, a first calculation module 120, a second calculation module 130, a third calculation module 140, and an optimization module 150, which are implemented by the modules 110-150. The functions or operational steps are similar to the above, and are not described in detail here, exemplarily, for example:

The collecting module 110 is configured to collect the positioning information of the first mobile terminal 21 at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal 21 at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal 21. ;

The first calculation module 120 is configured to calculate a latitude and longitude hash value of the current location of the first mobile terminal 21, and take a result of the first preset level of the hash value, and the first mobile terminal according to the result of the first preset level 21 The list of Wi-Fi hotspots scanned at the current location is aggregated in multiple business districts;

The second calculation module 130 is configured to calculate a latitude and longitude hash value of the current location of the first mobile terminal 21, and take a result of the second preset level of the hash value, and determine the location according to the result of the second preset level. a concentrated area of Wi-Fi hotspots in multiple business districts;

The third calculation module 140 is configured to read historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculate a first user of the first mobile terminal 21 to be in the multiple shopping districts. User satisfaction of Wi-Fi hotspots; and

The optimization module 150 is configured to filter out a second business circle from the plurality of business circles in response to a click operation of the second user in the second mobile terminal 22 to select a first business circle from the plurality of shopping circles. The number of first users in the plurality of business districts is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the first user The relationship between the numbers determines the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle. According to the traffic aggregation area and the Wi-Fi hotspot concentration area in the first business circle, the first business circle user is determined to be improved. Satisfaction needs to adjust the location of the Wi-Fi hotspot.

In addition, the present application also provides a Wi-Fi hotspot deployment optimization method. Referring to FIG. 3, it is a flowchart of a preferred embodiment of a Wi-Fi hotspot deployment optimization method of the present application. The method can be performed by a server, which can be implemented by software and/or hardware.

In this embodiment, the Wi-Fi hotspot deployment optimization method includes: Step S10 to Step S60.

In step S10, the location information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location are collected, where the location information includes the latitude and longitude of the current location of the first mobile terminal;

Step S20, calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the first preset level of the hash value, and scanning the first mobile terminal at the current location according to the result of the first preset level. Wi-Fi hotspot lists are aggregated across multiple business districts;

Step S30, calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the second preset level of the hash value, and determining a Wi-Fi hotspot in the plurality of business circles according to the result of the second preset level Concentrated area

Step S40: Read historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculate a user of the first mobile terminal to the Wi-Fi hotspot in the multiple shopping districts. Satisfaction; and

Step S50: In response to the click operation of the second user selecting a first business circle from the plurality of shopping circles, the second user selects a second business circle from the plurality of business circles, the second business The number of first users in the plurality of business circles is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the number of first users Correlation relationship, determine the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle. According to the traffic flow aggregation area and the Wi-Fi hotspot concentration area in the first business circle, it is determined that the user satisfaction of the first business circle needs to be adjusted. The location of the Wi-Fi hotspot.

In this embodiment, each city has a plurality of different business districts, wherein the business circle refers to a certain range of regions, and the first user refers to accessing and using the Wi-Fi hotspots in each commercial circle through the first mobile terminal. User, the second user refers to the staff of the Wi-Fi hotspot provider, and the second user passes the second mobile terminal. Solving the distribution of Wi-Fi hotspots in each business circle and the user satisfaction of the first user to Wi-Fi hotspots in each business circle. The first mobile terminal is equipped with an APP for connecting to a Wi-Fi hotspot, and the APP can be obtained. The location information (latitude and longitude) of the first mobile terminal at the current location, and the client program of the Wi-Fi hotspot deployment optimization program is installed on the second mobile terminal. Hotspot vendors can use a variety of channels to understand the areas where the first users of each city's business districts gather, such as obtaining relevant data through third parties.

When it is required to optimize the deployment of the Wi-Fi hotspot in a certain business circle, the APP scans the Wi-Fi hotspot list available at the current location through the first mobile terminal, and collects all the Wi-Fi hotspots in the Wi-Fi hotspot list. Historical data within a preset time (one week), including: Wi-Fi name, time of access, time of operation, operation status (connection success, connection failure, login success, login failure, etc.), frequency of access, availability of operators, etc. And then send the above historical data to the server. The server extracts key historical data, such as Wi-Fi identification, time, location, connection operation, Internet access duration, number of successful connections, and number of connection failures, through the data collection technology (Extract-Transform-Load, ETL). The number of retries, the number of successful logins, the number of failed logins, etc., are saved to the memory for subsequent user satisfaction calculation operations.

It can be understood that when the first mobile terminal scans the available Wi-Fi hotspot list at a certain location, the transmitting device of the Wi-Fi hotspot (hereinafter referred to as Wi-Fi hotspot) in the Wi-Fi hotspot list is also located. The location of the first mobile terminal is located, and therefore, the location of the Wi-Fi hotspot can be estimated according to the location information of the first mobile terminal. It should be understood that the geohash algorithm can be used to calculate the latitude and longitude hash values, and the hash values of different levels can be different. For example, one to nine results can be taken, and the six-level result is expressed as a range of 1.2 km*1.2 km. (Approximately can be understood as the scope of a business circle), taking a seven-level result indicating a range of 152m * 152m.

Taking the first mobile terminals A, B, C, D, and E as an example, the Wi-Fi hotspot lists scanned by the first mobile terminal at the current location are a, b, c, d, and e, respectively, assuming a first preset. The level is six levels, the server reads the latitude and longitude of the current position of the first mobile terminal A, B, C, D, E from the memory, performs a geohash operation, calculates the latitude and longitude hash value of the current position of each first mobile terminal, and takes a hash. If the six-level hash value of the first mobile terminal A, B, C, D, and E is the same, it is determined that the first mobile terminal A, B, C, D, and E are in the same business circle, correspondingly The Wi-Fi hotspots in the Wi-Fi lists a, b, c, d, and e are also located in the business district.

After the pre-determination of the Wi-Fi hotspot in the business circle, the second calculation step is needed to determine the area of the Wi-Fi hotspot in the business circle. Specifically, the second calculating step includes: according to the second preset level. As a result, the Wi-Fi hotspot list in each business district is divided into different regional blocks smaller than the business circle; in the Wi-Fi hotspot list in the different regional blocks, Wi-s with the same Wi-Fi hotspot will be The Fi hotspot list is merged to form a new Wi-Fi hotspot list; the different regional blocks in which the Wi-Fi hotspot list with the same Wi-Fi hotspot is located are merged to form a new regional block, and different Wi-Fi hotspots in the new local block are determined. The number of Wi-Fi hotspots in each business district is based on the number of Wi-Fi hotspots in the new block of the business district.

Assuming that the second preset level is seven, performing a geohash operation on the latitude and longitude of the current location of the first mobile terminal A, B, C, D, and E, and taking a seven-level result of the hash value, wherein the first mobile terminal The seventh-level results of A and C are the same. The seven-level results of the first mobile terminals B and E are the same. The Wi-Fi hotspots in the Wi-Fi hotspot list a and c are divided into the regional block P, and Wi-Fi is used. The plurality of Wi-Fi hotspots in the hotspot list b, e are divided into the regional block Q, and the plurality of Wi-Fi hotspots in the Wi-Fi hotspot list d are separately divided into the regional block O. If there are duplicate Wi-Fi hotspots in the Wi-Fi hotspot list in the same area block, deduplication is performed on the Wi-Fi hotspots in each of the two Wi-Fi hotspot lists, and the two Wis after deduplication are performed. -Fi hotspot list merges into one Wi-Fi hotspot list until there is no duplicate Wi-Fi hotspot between each Wi-Fi hotspot list in the same block, that is, if there is originally 20 in a certain block A list of Wi-Fi hotspots, after deduplication, the number of Wi-Fi hotspot lists will be less than or equal to 20.

It can be understood that, assuming that the transmitting device of a Wi-Fi hotspot is located between two points, and both points are within the coverage of the Wi-Fi hotspot, then different first mobile terminals located between the two points Both Wi-Fi hotspots can be scanned, that is, according to the latitude and longitude in different first mobile terminal positioning information, the same Wi-Fi hotspot may be divided into the vicinity of the middle line of two adjacent different regional blocks. Wi-Fi hotspots, therefore, need to further process this type of Wi-Fi hotspot. Assuming that the area blocks P and Q are adjacent, and the same Wi-Fi hotspot exists in the Wi-Fi hotspot list in the area blocks P and Q, then the area blocks P and Q are merged into a new area block, and De-duxing the Wi-Fi hotspots in all Wi-Fi hotspot lists in this new block, maximizing the number of Wi-Fi hotspots in the new block; then, in multiple new blocks The Wi-Fi hotspots are merged and de-duplicated until there are no duplicate Wi-Fi hotspots in all the blocks in the business circle and in the block. There are many cases, and the number of new blocks is relatively small. The range of new blocks is different. The number of Wi-Fi hotspots in each new block is different. Some of the new blocks have a large number of Wi-Fi hotspots, and some have few Wi-Fi. The obtained distribution of each block and the number of Wi-Fi hotspots in each block are linked to the electronic map of the business circle, so that the area where the Wi-Fi hotspot is concentrated in the business circle can be determined.

S=C*L*T ₁ /(T ₂ ^1/9 )

The Wi-Fi operator may collect a first user's user satisfaction sample for the Wi-Fi hotspot in the business circle through an operation questionnaire or a user scoring system, and the predetermined logistic regression model is used to calculate the first user to each business circle. User satisfaction of the internal Wi-Fi hotspot, the model file of the logistic regression model is stored in the memory, which can be collected through the collected user satisfaction sample and the key historical data of the Wi-Fi hotspot within the business circle in the past three months. Trained.

It should be noted that the advantage of the offline training model is that it utilizes a large amount of historical data, and the sample is sufficient. The advantage of the online training model is that it can use the latest data, the model can adapt to the changes of real-time data, and the online model is more accurate in the case of large data distribution and historical gap. In order to make the user satisfaction of the Wi-Fi hotspots in each commercial circle obtained in the subsequent calculation more accurate, the above-mentioned logistic regression model can be updated every three days. Then, the key historical data of the Wi-Fi hotspot in each business circle in the last week is read from the memory, and the updated logistic regression model is input, and the first user's user satisfaction with the Wi-Fi hotspot in the business circle is calculated. By combining offline training and online training, the advantages of both can be taken to improve the accuracy of the model, and at the same time, the problem of too little data volume or real-time model update failure caused by network and system problems is prevented in the online environment. There is already a mature calculation method for training and updating the model and using it to calculate the user satisfaction of Wi-Fi hotspots in each business circle, and will not be described here.

Further, an electronic map is installed on the second mobile terminal, and the map of all cities is displayed to the second user through the electronic map, and when the second user selects a certain city, the location and the business districts of all the business districts of the city are also displayed. User satisfaction within the Wi-Fi hotspot. When a Wi-Fi hotspot provider needs to optimize the deployment of Wi-Fi hotspots in a certain business circle to improve the user satisfaction of Wi-Fi hotspots in the business circle, select the business circle, and the server will respond to the click operation to For example, in the business circle B, the number of the first user is a, and the server selects the user satisfaction from the number of the first user and the current number of the first user of the business circle B (for example, a±50). The highest business circle G, according to the relationship between the number of Wi-Fi hotspots in the business circle G and the number of first users, determine whether the Wi-Fi hotspot should be increased or decreased in the business circle B, and then according to the traffic flow area in the business circle B and The concentrated areas of the Wi-Fi hotspots in the business district B are compared, and it is determined that the location of the Wi-Fi hotspot needs to be adjusted in the business circle B.

Specifically, if the number of Wi-Fi hotspots in the business circle G (for example, m) is significantly more than the number of Wi-Fi hotspots in the business circle B (for example, n), then the corresponding number (mn) needs to be added in the business circle B. The Wi-Fi hotspot is equal to the number of Wi-Fi hotspots in the business district G; if the number of Wi-Fi hotspots in the business circle G is less than B or equivalent, the number of Wi-Fi hotspots does not cause the business circle B, The main reason for the difference in user satisfaction is to consider whether the location of the Wi-Fi hotspot is reasonable.

It can be understood that for the area where the traffic volume in the business circle is concentrated, the demand for the Wi-Fi hotspot is also relatively large. Then, after reading the distribution area of the traffic flow in the business circle B obtained from the third party from the memory 11 The comparison between the traffic aggregation area in the business circle B and the centralized area of the Wi-Fi hotspot in the business circle B obtained through the second calculation step is the same. If the centralized area of the first user aggregation area and the Wi-Fi hotspot is inconsistent, the business is The first user aggregation area of circle B has fewer Wi-Fi hotspots, and there are more Wi-Fi hotspots in the area where there are fewer first users, so it is necessary to adjust some Wi-Fi hotspots from the area where the first user is less to the first user. Aggregation area, if the first user aggregation area and the centralized area of the Wi-Fi hotspot are consistent, then Ming may be a quality problem in the Wi-Fi hotspot in the business district B. It is recommended to replace the Wi-Fi hotspot.

It should be noted that the preset time and the like need to be preset parameters, which can be adjusted according to user needs.

In other embodiments, the method further includes: displaying a concentrated area of the Wi-Fi hotspot in the first business circle on the electronic map of the second mobile terminal, and displaying Wi-Fi that needs to be adjusted to improve user satisfaction in the first business circle. The number of hotspots and the location of Wi-Fi hotspots.

The server displays the distribution of the Wi-Fi hotspots in the business circle to the second user through the first display area of the second mobile terminal, and displays the Wi-Fi hotspot user in the business circle B in the second display area of the second mobile terminal. Satisfaction adjustment scheme for Wi-Fi hotspots. The first display area and the second display area are only different to indicate that the two display areas are different.

The Wi-Fi hotspot deployment optimization method proposed by the foregoing embodiment obtains the historical data of all the Wi-Fi hotspots scanned by the first mobile terminal, and calculates the user's satisfaction with the Wi-Fi hotspots of each commercial circle, and the Wi in each business circle. The aggregation area of the Fi hotspot is based on the calculation result, and the optimization scheme for the Wi-Fi hotspot deployment in the business circle with lower user satisfaction is given, and the Wi-Fi hotspot coverage population is increased to improve the user's online experience.

In addition, the embodiment of the present application further provides a computer readable storage medium, where the Wi-Fi hotspot deployment optimization program is stored, and when the optimization program is executed by the processor, the following operations are implemented:

The specific implementation manner of the computer-readable storage medium of the present application is substantially the same as the specific implementation manner of the foregoing Wi-Fi hotspot deployment optimization method, and details are not described herein again.

It is to be understood that the term "comprises", "comprising", or any other variants thereof, is intended to encompass a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a series of elements includes those elements. It also includes other elements not explicitly listed, or elements that are inherent to such a process, device, item, or method. An element that is defined by the phrase "comprising a ..." does not exclude the presence of additional equivalent elements in the process, the device, the item, or the method that comprises the element.

The serial numbers of the embodiments of the present application are merely for the description, and do not represent the advantages and disadvantages of the embodiments. Through the description of the above embodiments, those skilled in the art can clearly understand that the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better. Implementation. Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM as described above). , a disk, an optical disk, including a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the methods described in the various embodiments of the present application.

The above is only a preferred embodiment of the present application, and is not intended to limit the scope of the patent application, and the equivalent structure or equivalent process transformations made by the specification and the drawings of the present application, or directly or indirectly applied to other related technical fields. The same is included in the scope of patent protection of this application.

Claims

A Wi-Fi hotspot deployment optimization method is applied to a server, and the method includes:

The acquiring step: collecting the positioning information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal;

a first calculating step: calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the first preset level of the hash value, and scanning the first mobile terminal at the current location according to the result of the first preset level The list of Wi-Fi hotspots is aggregated in multiple business districts;

a second calculating step: calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the second preset level of the hash value, and determining, according to the result of the second preset level, the Wi- in the plurality of shopping districts a concentrated area of Fi hotspots;

a third calculating step: reading historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculating, by the first user of the first mobile terminal, the Wi-Fi hotspot in the multiple shopping districts User satisfaction; and

An optimization step of: selecting, in the second mobile terminal, a click operation of selecting a first business circle from the plurality of shopping circles, and screening a second business circle from the plurality of business circles, the second business The number of first users in the plurality of business circles is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the number of first users Correlation relationship, determine the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle. According to the traffic flow aggregation area and the Wi-Fi hotspot concentration area in the first business circle, it is determined that the user satisfaction of the first business circle needs to be adjusted. The location of the Wi-Fi hotspot.
The Wi-Fi hotspot deployment optimization method according to claim 1, wherein the method further comprises:

Demonstration step: displaying the concentrated area of the Wi-Fi hotspot in the first business circle on the electronic map of the second mobile terminal, and displaying the number of Wi-Fi hotspots and Wi-Fi hotspots that need to be adjusted to improve the satisfaction of the first business circle user position.
The Wi-Fi hotspot deployment optimization method according to claim 2, wherein the second calculating step comprises:

According to the result of the second preset level, the Wi-Fi hotspot list in each business circle is divided into different regional blocks smaller than the business circle;

In the Wi-Fi hotspot list in the different area blocks, the Wi-Fi hotspot lists with the same Wi-Fi hotspot are merged to form a new Wi-Fi hotspot list;

Merging different area blocks in which the Wi-Fi hotspot list with the same Wi-Fi hotspot is located to form a new area block, and determining the number of Wi-Fi hotspots in different new area blocks;

Get Wi-Fi in each business district based on the number of Wi-Fi hotspots in the new block of the business district The area where the hotspots are concentrated.
The Wi-Fi hotspot deployment optimization method according to claim 3, wherein the third calculating step comprises:

According to the historical data in the preset time, each user index of the Wi-Fi hotspot in each business circle is calculated, and the weighted summary is the user satisfaction of the first user, and the calculation formula is:

S=C*L*T 1 /(T 2 1/9 )

Among them, S is the first user's satisfaction with the Wi-Fi hotspots in each business circle, C is the average connection success rate of Wi-Fi hotspots in each business circle, and L is the average landing of Wi-Fi hotspots in each business circle. Success rate, T 1 is the average online time of Wi-Fi hotspots in each business circle, and T 2 is the average connection of Wi-Fi hotspots in each business circle to power consumption.
The Wi-Fi hotspot deployment optimization method according to claim 4, wherein the third calculating step is replaced by:

According to the historical data of the Wi-Fi hotspots in each business district within a preset time period and a predetermined logistic regression model, the first user's user satisfaction with the Wi-Fi hotspots in each business circle is calculated.
The Wi-Fi hotspot deployment optimization method according to claim 5, wherein the optimizing step comprises:

When the number of Wi-Fi hotspots in the first business circle is less than the number of Wi-Fi hotspots in the second business circle, increase the number of Wi-Fi hotspots in the first business circle; and

Obtain the traffic distribution of the first business circle. When the traffic aggregation area and the Wi-Fi hotspot concentration area in the first business circle are inconsistent, the new Wi-Fi hotspot is set in the traffic flow aggregation area in the first business circle. .
The Wi-Fi hotspot deployment optimization method according to claim 4, wherein the optimizing step comprises:

When the number of Wi-Fi hotspots in the first business circle is less than the number of Wi-Fi hotspots in the second business circle, increase the number of Wi-Fi hotspots in the first business circle; and

Obtain the traffic distribution of the first business circle. When the traffic aggregation area and the Wi-Fi hotspot concentration area in the first business circle are inconsistent, the new Wi-Fi hotspot is set in the traffic flow aggregation area in the first business circle. .
A server, comprising: a memory, a processor, wherein the memory stores a Wi-Fi hotspot deployment optimization program, and when the optimization program is executed by the processor, the following steps are implemented:

The acquiring step: collecting the positioning information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal;

a first calculating step: calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the first preset level of the hash value, and scanning the first mobile terminal at the current location according to the result of the first preset level The list of Wi-Fi hotspots is aggregated in multiple business districts;

a second calculating step: calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the second preset level of the hash value, and determining, according to the result of the second preset level, the Wi- in the plurality of shopping districts a concentrated area of Fi hotspots;

a third calculating step: reading historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculating, by the first user of the first mobile terminal, the Wi-Fi hotspot in the multiple shopping districts User satisfaction; and

An optimization step of: selecting, in the second mobile terminal, a click operation of selecting a first business circle from the plurality of shopping circles, and screening a second business circle from the plurality of business circles, the second business The number of first users in the plurality of business circles is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the number of first users Correlation relationship, determine the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle. According to the traffic flow aggregation area and the Wi-Fi hotspot concentration area in the first business circle, it is determined that the user satisfaction of the first business circle needs to be adjusted. The location of the Wi-Fi hotspot.
The server according to claim 8, wherein the optimization program is further executed by the processor to:

Demonstration step: displaying the concentrated area of the Wi-Fi hotspot in the first business circle on the electronic map of the second mobile terminal, and displaying the number of Wi-Fi hotspots and Wi-Fi hotspots that need to be adjusted to improve the satisfaction of the first business circle user position.
The server according to claim 9, wherein said second calculating step comprises:

According to the result of the second preset level, the Wi-Fi hotspot list in each business circle is divided into different regional blocks smaller than the business circle;

In the Wi-Fi hotspot list in the different area blocks, the Wi-Fi hotspot lists with the same Wi-Fi hotspot are merged to form a new Wi-Fi hotspot list;

Merging different area blocks in which the Wi-Fi hotspot list with the same Wi-Fi hotspot is located to form a new area block, and determining the number of Wi-Fi hotspots in different new area blocks;

According to the number of Wi-Fi hotspots in the new block of the business district, the area where Wi-Fi hotspots are concentrated in each business district is obtained.
The server according to claim 10, wherein said third calculating step comprises:

Calculate the user indicators of the Wi-Fi hotspots in each business circle of the first user according to the historical data in the preset time period, and weight the aggregated user satisfaction of the first user. The calculation formula is:

S=C*L*T 1 /(T 2 1/9 )

Among them, S is the first user's satisfaction with the Wi-Fi hotspots in each business circle, C is the average connection success rate of Wi-Fi hotspots in each business circle, and L is the average landing of Wi-Fi hotspots in each business circle. Success rate, T 1 is the average online time of Wi-Fi hotspots in each business circle, and T 2 is the average connection of Wi-Fi hotspots in each business circle to power consumption.
The server according to claim 11, wherein said third calculating step is replaceable by:

According to the historical data of the Wi-Fi hotspots in each business district within a preset time period and a predetermined logistic regression model, the first user's user satisfaction with the Wi-Fi hotspots in each business circle is calculated.
The server according to claim 12, wherein said optimizing step comprises:

When the number of Wi-Fi hotspots in the first business circle is less than the number of Wi-Fi hotspots in the second business circle, increase the number of Wi-Fi hotspots in the first business circle; and

Obtain the traffic distribution of the first business circle. When the traffic aggregation area and the Wi-Fi hotspot concentration area in the first business circle are inconsistent, the new Wi-Fi hotspot is set in the traffic flow aggregation area in the first business circle. .
The server according to claim 11, wherein said optimizing step comprises:

When the number of Wi-Fi hotspots in the first business circle is less than the number of Wi-Fi hotspots in the second business circle, increase the number of Wi-Fi hotspots in the first business circle; and

Obtain the traffic distribution of the first business circle. When the traffic aggregation area and the Wi-Fi hotspot concentration area in the first business circle are inconsistent, the new Wi-Fi hotspot is set in the traffic flow aggregation area in the first business circle. .
A computer readable storage medium, wherein the computer readable storage medium stores a Wi-Fi hotspot deployment optimization program, and when the optimization program is executed by the processor, the following steps are implemented:

The acquiring step: collecting the positioning information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal;

a first calculating step: calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the first preset level of the hash value, and scanning the first mobile terminal at the current location according to the result of the first preset level The list of Wi-Fi hotspots is aggregated in multiple business districts;

a second calculating step: calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the second preset level of the hash value, and determining, according to the result of the second preset level, the Wi- in the plurality of shopping districts a concentrated area of Fi hotspots;

a third calculating step: reading historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculating, by the first user of the first mobile terminal, the Wi-Fi hotspot in the multiple shopping districts User satisfaction; and

An optimization step of: selecting, in response to the second user, a second one from the plurality of shopping circles at the second mobile terminal Clicking a business circle to select a second business circle from the plurality of business circles, the first number of users in the plurality of business circles and the first number of users in the first business circle The user satisfaction is the highest. According to the relationship between the number of Wi-Fi hotspots in the second business district and the number of first users, the number of Wi-Fi hotspots that need to be adjusted to improve the satisfaction of the first business circle is determined. The traffic concentration area and the Wi-Fi hotspot concentration area in a business circle determine the location of the Wi-Fi hotspot that needs to be adjusted to improve the user satisfaction of the first business circle.
The computer readable storage medium according to claim 15, wherein the optimization program is further executed by the processor to:

Demonstration step: displaying the concentrated area of the Wi-Fi hotspot in the first business circle on the electronic map of the second mobile terminal, and displaying the number of Wi-Fi hotspots and Wi-Fi hotspots that need to be adjusted to improve the satisfaction of the first business circle user position.
The computer readable storage medium of claim 16, wherein the second calculating step comprises:

According to the result of the second preset level, the Wi-Fi hotspot list in each business circle is divided into different regional blocks smaller than the business circle;

In the Wi-Fi hotspot list in the different area blocks, the Wi-Fi hotspot lists with the same Wi-Fi hotspot are merged to form a new Wi-Fi hotspot list;

Merging different area blocks in which the Wi-Fi hotspot list with the same Wi-Fi hotspot is located to form a new area block, and determining the number of Wi-Fi hotspots in different new area blocks;

According to the number of Wi-Fi hotspots in the new block of the business district, the area where Wi-Fi hotspots are concentrated in each business district is obtained.
The computer readable storage medium of claim 17, wherein the third calculating step comprises:

Calculate the user indicators of the Wi-Fi hotspots in each business circle of the first user according to the historical data in the preset time period, and weight the aggregated user satisfaction of the first user. The calculation formula is:

S=C*L*T 1 /(T 2 1/9 )

Among them, S is the first user's satisfaction with the Wi-Fi hotspots in each business circle, C is the average connection success rate of Wi-Fi hotspots in each business circle, and L is the average landing of Wi-Fi hotspots in each business circle. Success rate, T 1 is the average online time of Wi-Fi hotspots in each business circle, and T 2 is the average connection of Wi-Fi hotspots in each business circle to power consumption.
The computer readable storage medium of claim 18, wherein the third calculating step is replaceable by:

According to the historical data of the Wi-Fi hotspots in each business district within a preset time period and a predetermined logistic regression model, the first user's user satisfaction with the Wi-Fi hotspots in each business circle is calculated.
The computer readable storage medium of claim 19, wherein the optimizing step comprises:

When the number of Wi-Fi hotspots in the first business circle is less than the number of Wi-Fi hotspots in the second business circle, increase the number of Wi-Fi hotspots in the first business circle; and

Obtain the traffic distribution of the first business circle. When the traffic aggregation area and the Wi-Fi hotspot concentration area in the first business circle are inconsistent, the new Wi-Fi hotspot is set in the traffic flow aggregation area in the first business circle. .