CN118283677B

CN118283677B - Method and device for generating room layout and electronic equipment

Info

Publication number: CN118283677B
Application number: CN202211720259.4A
Authority: CN
Inventors: 骆佩佩; 宋敏; 周哲晅; 郑汉翔
Original assignee: Ruijie Networks Co Ltd
Current assignee: Ruijie Networks Co Ltd
Priority date: 2022-12-30
Filing date: 2022-12-30
Publication date: 2026-01-13
Anticipated expiration: 2042-12-30
Also published as: CN118283677A

Abstract

This application discloses a method, apparatus, and electronic device for generating room layouts, relating to the field of communication technology. The method includes: acquiring the average network signal strength of each terminal at different time periods; clustering the average network signal strength to obtain N clusters; identifying K fixed terminals from the N clusters; finally, labeling the K fixed terminals with room identifiers, and generating a first room layout map based on all the room identifiers. Based on the above method, by analyzing network data from various terminals in a home environment, it is possible to locate rooms using a single wireless access point (AP) and generate a home floor plan.

Description

Method and device for generating room layout and electronic equipment

Technical Field

The present application relates to the field of communications technologies, and in particular, to a method and an apparatus for generating a room layout, and an electronic device.

Background

With the continuous development of WiFi technology, users have also put higher demands on experience when WiFi is used. WiFi is a wireless local area network technology conforming to IEEE802.11 standard, and currently, a wireless Access Point (abbreviated as AP) has become a home necessary device for various intelligent terminals to Access the internet. However, when the wireless AP is affected by an obstacle, such as a wall, a door, a cabinet, etc., the WiFi signal may be reduced, and the wireless AP may not adjust the WiFi signal to strengthen the signal of the room with weaker signal.

In the prior art, in order to complete signal coverage analysis of a wireless AP, a family pattern map is usually used in a signal thermodynamic diagram, but the family pattern map used at this time is generally obtained through purchase or drawn by a user. After the user makes an adjustment to the household pattern in the household, for example, when a cabinet, a door and the like are additionally arranged in a room to prevent the transmission of WiFi signals, the wireless AP cannot sense the change in the room, the reference value of the wireless AP is reduced through the signal coverage analysis finished by the purchased household pattern, the wireless AP cannot complete the signal coverage analysis according to the household pattern, and therefore, when the WiFi signals are abnormal, abnormal rooms cannot be quickly positioned, and the network utilization experience of the user is poor.

By judging the common room of the terminal equipment, a more visual analysis basis is provided when a manager positions the network environment problem of the user, and the analysis of the network environment of the home cannot be realized through one wireless AP in the existing method to obtain the family pattern diagram.

Disclosure of Invention

The application provides a method, a device and electronic equipment for generating a room layout, which are characterized in that terminals with similar signal strength are divided into the same cluster through a clustering algorithm by acquiring WiFi radio frequency intensity values of all terminals in a room, and the room where a fixed terminal is located is obtained by utilizing the maximum complete subgraph among the fixed terminals, so that the room layout diagram is generated by positioning the room.

In a first aspect, the present application provides a method of generating a room layout, the method comprising:

Acquiring the average value of the network signal intensity of each terminal in different time periods, wherein the average value of the network signal intensity of each terminal is the average value when the network signal of each terminal keeps a stable state;

Clustering the signal intensity mean values of the networks to obtain N clusters, wherein N is an integer greater than 1;

k fixed terminals are determined from the N clusters, wherein the K fixed terminals belong to different clusters, and K is an integer greater than or equal to 0;

and labeling room identifications for the K fixed terminals, and generating a first room layout diagram based on all the room identifications.

By the method, different rooms with similar signals in the family can be better distinguished by utilizing the similarity of the WiFi radio frequency intensity values among the terminals, so that the room layout diagram is generated by positioning the rooms.

In an alternative embodiment, obtaining the average value of the network signal strength of each terminal in different time periods includes:

Acquiring network signal intensity values of the terminals in different time periods, wherein the network signal intensity values do not comprise network signal intensity values with jump in a stable state;

and obtaining the network signal intensity mean value of each terminal in different time periods according to the network signal intensity value.

In an optional implementation manner, the clustering processing is performed on the average value of the signal intensity of each network to obtain N clusters, which includes:

forming corresponding feature vectors according to the network intensity mean value of each terminal;

and clustering each feature vector through a clustering algorithm to obtain N clustering clusters.

Through the method, the terminals with similar signals are divided into the same cluster by adopting a clustering algorithm, so that the preliminary positioning of the room can be realized.

In an optional implementation manner, the determining K fixed terminals in the N clusters includes:

determining J fixed terminals in the N cluster groups;

Grouping the J fixed terminals pairwise, and creating a relation matrix of the J fixed terminals according to grouping results;

and calculating the maximum complete subgraph corresponding to the J fixed terminals through the relation matrix, and determining K fixed terminals in the maximum complete subgraph.

By the method, the uncorrelated relation among the terminals is obtained by adopting the maximum complete subgraph, and further the fixed terminal corresponding to each room can be obtained.

In an optional implementation manner, after labeling room identifiers for the K fixed terminals and generating the first room layout based on all the room identifiers, the method further includes:

Acquiring the cluster identifiers of the K fixed terminals and the cluster identifiers of the mobile terminals;

judging whether the cluster identifier of the mobile terminal is the same as any cluster identifier in the cluster identifiers of the K fixed terminals;

if not, adding a room identifier on the basis of the first room layout diagram to generate a second room layout diagram.

By the method, the room where the fixed terminal is located is obtained by utilizing the maximum complete subgraph, and the room which is not positioned successfully can be further obtained according to the clustering relation between the mobile terminal and the fixed terminal, so that a complete room layout diagram of the whole environment is generated.

In a second aspect, the present application provides an apparatus for generating a room layout, the apparatus comprising:

the acquisition module is used for acquiring the network signal intensity mean value of each terminal in different time periods;

The processing module is used for carrying out clustering processing on the signal intensity mean values of the networks to obtain N clustering clusters;

the determining module is used for determining K fixed terminals in the N clustering clusters;

and the generating module is used for labeling room identifications for the K fixed terminals and generating a first room layout diagram based on all the room identifications.

In an alternative embodiment, the obtaining module is specifically configured to:

In an alternative embodiment, the processing module is specifically configured to:

In an alternative embodiment, the determining module is specifically configured to:

determining J fixed terminals in the N cluster groups;

In an alternative embodiment, the generating module is further configured to:

In a third aspect, the present application provides an electronic device, comprising:

a memory for storing a computer program;

and a processor for implementing the steps of one of the methods for generating a room layout described above when executing the computer program stored on the memory.

In a fourth aspect, the present application provides a computer readable storage medium having a computer program stored therein, which when executed by a processor, implements the steps of a method of generating a room layout as described above.

The technical effects of each of the second to fourth aspects and the technical effects that may be achieved by each of the aspects are referred to above for the technical effects that may be achieved by each of the first aspect and the various possible aspects of the first aspect, and the detailed description is not repeated here.

Drawings

Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present application;

FIG. 2 is a flow chart of a method for generating a room layout according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a clustering result provided in an embodiment of the present application;

FIG. 4 is a schematic diagram of an effect of generating a room layout according to an embodiment of the present application;

FIG. 5 is a schematic diagram of an apparatus for generating a room layout according to an embodiment of the present application;

Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings. The specific method of operation in the method embodiment may also be applied to the device embodiment or the system embodiment. In the description of the present application, "a plurality of" means "at least two". "and/or" describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate that there are three cases of a alone, a and B together, and B alone. A and B are connected, and it can be represented that A and B are directly connected and A and B are connected through C. In addition, in the description of the present application, the words "first," "second," and the like are used merely for distinguishing between the descriptions and not be construed as indicating or implying a relative importance or order.

Embodiments of the present application will be described in detail below with reference to the accompanying drawings.

With the continuous development of WiFi technology, users have also put higher demands on experience when WiFi is used. WiFi is a wireless local area network technology conforming to the IEEE802.11 standard, and at present, wireless AP has become a necessary home device for various intelligent terminals to access the Internet. However, when the wireless AP is affected by an obstacle, such as a wall, a door, a cabinet, etc., the WiFi signal may be reduced, and the wireless AP may not adjust the WiFi signal to strengthen the signal of the room with weaker signal.

By judging the common room of the terminal equipment, a more visual analysis basis is provided when an operator positions the problem of the network environment of the user, and the analysis of the network environment of the home cannot be realized through one wireless AP in the existing method to obtain the family pattern diagram.

In view of this, as shown in fig. 1, in a home environment, a wireless AP generally provides a wireless network for each terminal, and uses network data generated by each terminal to locate a room where each terminal is located, so as to generate a room layout, and an embodiment of the present application provides a method for generating a room layout, which specifically includes: firstly, acquiring network signal intensity average values of all terminals in different time periods, then clustering all the network signal intensity average values to obtain N clustering clusters, further determining K fixed terminals in the N clustering clusters respectively, labeling room identifications for the K fixed terminals, and generating a first room layout diagram based on all the room identifications. Through the method, the network signal intensity mean value of each terminal is divided into a plurality of clusters according to the similarity, and the fixed terminal is further determined in each cluster, so that the positioning of each room can be realized. Thus, the positioning of each room in the home environment can be realized through 1 wireless AP, and then the room layout diagram is generated.

The method and the device according to the embodiments of the present application are based on the same technical concept, and because the principles of the problems solved by the method and the device are similar, the embodiments of the device and the method can be referred to each other, and the repetition is not repeated.

As shown in fig. 2, a flowchart of a method for generating a room layout according to an embodiment of the present application specifically includes the following steps:

S1, acquiring the network signal intensity average value of each terminal in different time periods;

In the embodiment of the application, in order to determine the room in which each terminal is located, a large amount of data is required. Therefore, firstly, the average value of the network signal intensity of each terminal in different time periods is required to be obtained, wherein the different time periods are particularly time periods when the network signal intensity value of each terminal is stable and has no abrupt change, for example, the network signal intensity value of the mobile phone is stabilized at about-60 db in the time period from ten points to thirty minutes, the network signal intensity value of the time period can be averaged, but the network signal intensity value of the mobile phone is severely fluctuated at about-80 db, the network signal intensity value when the intense fluctuation occurs cannot be calculated in the average value, and if the network signal intensity value of the mobile phone is restored to be stable after a period of time, for example, the network signal intensity value of the mobile phone is stabilized at about-62 db in thirty-five minutes after a period of time, the network signal intensity value of the mobile phone is considered to be stabilized and the network signal intensity value of the time period can be averaged. In particular, devices capable of using WiFi in a home environment include a variety of devices, including fixed terminals as well as mobile terminals. For example, a fixed terminal such as a camera and a television set, and a mobile terminal such as a mobile phone and a tablet computer are arranged in a room. When various devices are used, the quality of the network is related to a WiFi radio frequency signal strength value (RSSI for short), and the distance between a terminal and a wireless AP and the size of the RSSI value can be influenced by obstacles in a room.

The number of the RSSI averages which can be obtained by each terminal is not fixed, and the lengths of different time periods are not fixed, so that the RSSI averages are determined according to actual use conditions, and the judgment is specifically carried out according to whether the current network signal has a severe change.

Further, RSSI means of different terminals in different time periods are obtained. Specifically, when the terminal uses WiFi, its RSSI value may change with time and space changes.

Therefore, when the RSSI average value of each terminal is obtained, the RSSI average value is obtained while the network signal of each terminal is kept in a stable state. For example, when a user uses the mobile phone in a lying state, the RSSI value of the mobile phone may be about-60 db, the RSSI value may not be kept unchanged all the time during the use, and when a small signal jitter occurs, the RSSI value may be considered to be in a stable state. The nature of the WiFi signal is electromagnetic, and when the main lying door is closed, the WiFi signal will be disturbed, and the WiFi signal sent from the wireless AP will be reflected by the door. At this time, the RSSI value of the mobile phone is reduced, for example, from-60 db to-65 db. Here, the RSSI value is negative, and a larger value indicates a better WiFi signal.

Further, RSSI average values of the terminals in different time periods are obtained. Specifically, the RSSI values of the terminals in the time periods are obtained, and then the RSSI average value of the terminals in the different time periods is obtained according to the obtained RSSI values, so that the RSSI value when the terminal's RSSI value is obtained and the strong fluctuation is jumped cannot be calculated.

For example, when a tablet computer is used in a certain room, the RSSI value fluctuates around-70 db. At ten times, the RSSI value is-69 db, at ten times, the RSSI value is-70 db, at ten times, the RSSI value is-71 db, and therefore, the average RSSI value of the tablet personal computer in the time period from ten times to twenty times is-70 db.

When the room in which the tablet computer is located is in a door closing state, the WiFi signal is shielded by a door or other obstacles, and after the WiFi signal is reflected, the RSSI value is reduced. For example, after a room is closed at thirty minutes at ten points, the RSSI value is-75 db, at thirty-five minutes at ten points, the RSSI value is-76 db, at forty minutes at ten points, the RSSI value is-74 db, if the RSSI value at forty minutes at ten points is suddenly jumped, the RSSI value suddenly changes to-85 db, and the RSSI value at the time of jump cannot be used for averaging. From this, the mean value of RSSI after the door is closed or the RSSI value is reduced due to the shielding of other obstacles is-75 db. And if the RSSI value does not have severe fluctuation in a period of time, the received WiFi signal of the terminal is considered to be in a stable state.

And similarly, acquiring RSSI average values of other terminals in the room. Such as cameras, televisions, cell phones, audio equipment, etc.

S2, clustering the signal intensity mean values of the networks to obtain N clusters;

After the RSSI mean values of the terminals in different time periods are obtained, clustering the RSSI mean values to obtain N clustering clusters.

In an alternative embodiment, clustering is performed on each RSSI mean to obtain N clusters, including the following steps:

s201, forming corresponding feature vectors according to RSSI average values of all terminals;

s202, clustering each feature vector through a clustering algorithm to obtain N clustering clusters.

Specifically, after the RSSI mean values of different terminals are obtained in different time periods, each RSSI mean value is converted into a corresponding feature vector in an up-down sampling mode. The eigenvectors describe the main direction of transformation of the RSSI mean.

Further, all the feature vectors in different time periods are clustered through a clustering algorithm to obtain N clustering clusters. Specifically, in the embodiment of the application, a K-means (K-means clustering algorithm, abbreviated as K-means) clustering algorithm is adopted to divide the eigenvectors obtained by converting the RSSI mean into N classes.

First, the number of clusters is obtained using the Canopy algorithm. Specifically, canopy algorithm adopts a distance measurement method to find the centroid of the cluster, and finds a plurality of centroids of the eigenvectors formed by the RSSI mean of the corresponding fixed terminal from the eigenvectors formed by all the RSSI mean. The number of clusters obtained by the Canopy algorithm can be considered here as the number of rooms in which a fixed terminal is currently present. For example, the number of clusters is divided into 3. In the embodiment of the application, the feature vector can be divided for a plurality of times by using a K-means algorithm until 3 clusters are obtained. Wherein the number of clusters N is the same as the number of minimum distributions of rooms to be acquired.

Specifically, after the feature vectors corresponding to the RSSI averages are obtained, the number of clusters may be obtained through a Canopy algorithm. Further, for example, the number N of clusters is 3, and k=3 in the K-means algorithm, where the K-means algorithm is used to divide the feature vector formed by each RSSI average value into 3 clusters. In the embodiment of the application, the number of clusters is 3, the mass center of each cluster is found, and each cluster is required to be as close as possible to the mass center of the cluster in the cluster clusters obtained through the K-means algorithm division.

In the dividing process of the K-means algorithm, N data are selected in the dimension of each feature vector to obtain 3 centroids. After 3 centroids are selected, the Euclidean distance of each feature vector from the 3 centroids is calculated. Wherein the Euclidean distance is the true distance between two points in the multidimensional space.

After the Euclidean distance between each feature vector and the centroid is calculated, the Euclidean distance between each feature vector and each centroid is compared, and the feature vectors are further divided into clusters corresponding to the centroid with the smallest Euclidean distance, so that 3 clusters are obtained. Further, the centroids of the 3 clusters are determined. Specifically, the average value of all data of the dimension of each feature vector in each cluster is calculated, and the average value of each feature vector is used as the new centroid of each cluster.

After the new centroid of each cluster is obtained, the Euclidean distance from each feature vector to the new centroid is calculated, each cluster is subjected to new division, and the operation is repeated until the division result of the cluster where all the feature vectors are located is not changed any more, and the final N clusters can be obtained. Fig. 3 is a schematic diagram of a clustering result provided by an embodiment of the present application.

In particular, the average value of the network signal strength does not change too much in the actual use environment of the terminal. For example, when using Bluetooth sound in a study, the RSSI value may fluctuate within the range of-60 db, -61db or-62 db, but quickly return to a steady level. The RSSI value of the camera in the study also fluctuates within the range of-60 db, -61db or-62 db. Since the WiFi signal propagation paths of the bluetooth sound and the camera are substantially the same in the study environment, the RSSI values of the two are also substantially the same, and further, the bluetooth sound and the camera can be considered to be in the same room.

Under the condition of opening or closing the door, the network signal strength which can be received by the terminal is also different. When the door is opened, the network signal is better, the RSSI average value of the network signal is higher, and when the door is closed, the network signal is worse, and the RSSI average value of the network signal is correspondingly reduced. Therefore, for the same fixed terminal, the RSSI mean values in different time periods may be divided into different clusters, and the room where the fixed terminal is located is determined to be unchanged through the cluster identification, so that the room where the fixed terminal is located is fixed and cannot be changed due to occasional signal jitter division in different clusters.

For a mobile terminal, when the RSSI mean value of the mobile terminal is divided into different clusters in different time periods, the corresponding room will change, but the number of rooms obtained by clustering the RSSI mean value will not change.

Through the method, the RSSI mean value is formed into the feature vector, and each terminal with similar RSSI mean value is divided into the same cluster through the clustering algorithm, and each cluster represents a room.

S3, determining K fixed terminals in N clustering clusters;

in an alternative embodiment, determining K fixed terminals in N clusters, respectively, includes the following steps:

S301, determining J fixed terminals in N cluster groups;

s302, grouping J fixed terminals two by two, and creating a relation matrix of the J fixed terminals according to grouping results;

S303, calculating the maximum complete subgraph corresponding to the J fixed terminals through the relation matrix, and determining the K fixed terminals in the maximum complete subgraph.

Specifically, a fixed terminal and a mobile terminal in a home environment are divided into N clusters according to RSSI average values. Further, J fixed terminals are determined in the N clusters. For example, 4 fixed terminals are included in N clusters. In the embodiment of the application, when J fixed terminals are determined in N clusters, terminal identification service is introduced to determine that the terminals at the moment are fixed terminals and the terminals at the moment are mobile terminals.

Further, these 4 fixed terminals are grouped two by two. For example, fixed terminal 1 and fixed terminal 2 are divided into group a, and fixed terminal 3 and fixed terminal 4 are divided into group B. After the grouping is completed, a J relationship matrix is created. In the initial condition, the values in the matrix are all 0. For example, a 4 x 4 relationship matrix is created, with values in the matrix all being 0 in the initial condition. If the fixed terminal 1 and the fixed terminal 2 are divided into different clusters, it is considered that the fixed terminal 1 and the fixed terminal 2 are not in the same room, and further, positions of the fixed terminal 1 and the fixed terminal 2 corresponding to [1,2] and [2,1] in the relation matrix are filled with 1. If the fixed terminal 1 and the fixed terminal 2 are divided into the same cluster, the fixed terminal 1 and the fixed terminal 2 are considered to be in the same room, and the positions of the fixed terminal 1 and the fixed terminal 2 corresponding to [1,2] and [2,1] in the relation matrix are kept at 0.

The essence of calculating the maximum complete subgraph between the fixed terminals through the Hungary algorithm is to find the uncorrelated relationship between the terminals. For example, the fixed terminal 1 and the fixed terminal 2 are not in one room, the fixed terminal 2 and the fixed terminal 3 are not in one room, the fixed terminal 3 and the fixed terminal 4 are not in one room, and the fixed terminal 3 and the fixed terminal 1 are not in one room, so that the fixed terminal 1, the fixed terminal 2 and the fixed terminal 3 are respectively in different rooms.

It is thereby obtained that the fixed terminal 1, the fixed terminal 2, the fixed terminal 3 are in one separate room, respectively. Finally, it can be determined that three rooms of fixed terminals exist in the home environment.

The number of clusters N is not necessarily related to the number of fixed terminals J, when the number of fixed terminals is large, J may be larger than N, when the number of clusters is just equal to the number of fixed terminals, J is equal to N, or the number of fixed terminals is small, and some rooms have no fixed terminals, at this time, J may be smaller than N. And the number of the finally obtained K fixed terminals is smaller than or equal to the number of the clustering clusters N.

And obtaining the maximum complete subgraph according to the relation matrix of the J fixed terminals, and obtaining the number of the K independent fixed terminals according to the maximum complete subgraph.

S4, marking room identifiers for the K fixed terminals, and generating a room layout diagram based on all the room identifiers.

Firstly, the number of rooms corresponding to the fixed terminals is obtained by calculating the uncorrelated relation among all the fixed terminals. After determining the rooms in which each fixed terminal is located, the room corresponding to each fixed terminal is marked with a room identifier, for example, the room identifier of the room corresponding to the fixed terminal 1 is marked as room1, and the room identifier of the room corresponding to the fixed terminal 2 is marked as room2. If 4 rooms are located, the room identity is maximum room4.

K fixed terminals are determined by the maximum complete subgraph, each of which may represent a room. And labeling room identifiers for the K fixed terminals, and generating a first room layout diagram based on the room identifiers.

In an alternative embodiment, after labeling room identifiers for K fixed terminals and generating a first room layout based on all room identifiers, the method further includes the following steps:

s401, obtaining cluster identifiers of K terminals and cluster identifiers of mobile terminals;

s402, judging whether the cluster identifier of the mobile terminal is the same as any cluster identifier in the cluster identifiers of the K fixed terminals;

s403, if not, adding the room identification on the basis of the first room layout diagram to generate a second room layout diagram.

The cluster identification is identification for distinguishing different cluster, and the cluster identification of all terminals in the same cluster is the same.

In particular, the fixed terminal may be in the same room as the mobile terminal, or only the mobile terminal may be present in the room. And the cluster identification of the fixed terminal is acquired and compared with the cluster identification of the mobile terminal, and whether other rooms are not positioned successfully is judged. For example, if the cluster identifier of the camera 1 is a class a and the cluster identifier of the mobile phone 1 is also a class a, the camera 1 and the mobile phone 1 are considered to be in the same room. Further, the mobile phone 1 is marked with the same room identification as the camera 1. If the cluster identifier of the mobile phone 2 is H, in the clustering result, the cluster identifiers corresponding to the fixed terminals are B, C and D respectively. The cluster identifiers of the mobile phone B and each fixed terminal are different. So handset B is not in the same room as each fixed terminal.

Further, a new room identification is added on the basis of the existing first room layout, and an updated second room layout is generated based on the updated room identification.

Specifically, the number of rooms located by the fixed terminal is 3, the room identifiers are room1, room2 and room3 respectively, and further, the number of rooms located by the mobile terminal is increased on the basis of the original room identifiers. For example, the room identification is labeled room4 by the newly located room of the mobile terminal.

And finally, positioning all rooms through the fixed terminal and the mobile terminal, and generating an updated room layout according to the updated room identification. The final effect diagram of the method for generating the room layout provided by the embodiment of the application is shown in fig. 4.

Based on the same inventive concept, the embodiment of the present application further provides an apparatus for generating a room layout, as shown in fig. 5, where the apparatus includes:

the acquiring module 501 is configured to acquire network signal intensity averages of each terminal in different time periods;

The processing module 502 is configured to perform clustering on the signal intensity average values of the networks to obtain N clusters;

a determining module 503, configured to determine K fixed terminals in the N clusters;

The generating module 504 is configured to label room identifiers for the K fixed terminals, and generate a first room layout diagram based on all room identifiers.

determining J fixed terminals in the N cluster groups;

In an alternative embodiment, the generating module is further configured to:

It should be noted that, the above device provided in the embodiment of the present application can implement all the method steps in the method embodiment of generating the room layout, and can achieve the same technical effects, and detailed descriptions of the same parts and beneficial effects as those in the method embodiment in the embodiment are omitted.

Based on the same inventive concept, the embodiment of the present application further provides an electronic device, where the electronic device may implement the functions of the method for generating a room layout, and referring to fig. 6, the electronic device includes:

At least one processor 601, and a memory 602 connected to the at least one processor 601, the specific connection medium between the processor 61 and the memory 62 is not limited in the embodiment of the present application, and fig. 6 illustrates that the processor 601 and the memory 602 are connected through a bus 600. Bus 600 is shown in bold lines in fig. 6, and the manner in which the other components are connected is illustrated schematically and not by way of limitation. The bus 600 may be divided into an address bus, a data bus, a control bus, etc., and is represented by only one thick line in fig. 6 for convenience of representation, but does not represent only one bus or one type of bus. Alternatively, the processor 601 may be referred to as a controller, and the names are not limited.

In an embodiment of the present application, the memory 602 stores instructions executable by the at least one processor 601, and the at least one processor 601 may perform the method of generating a room layout as discussed above by executing the instructions stored by the memory 602. The processor 601 may implement the functions of the respective modules in the apparatus shown in fig. 5.

The processor 601 is a control center of the device, and various interfaces and lines can be used to connect various parts of the whole control device, and through running or executing instructions stored in the memory 602 and calling data stored in the memory 602, various functions of the device and processing data can be performed, so that the device can be monitored as a whole.

In one possible design, processor 601 may include one or more processing units, and processor 601 may integrate an application processor and a modem processor, wherein the application processor primarily processes operating systems, user interfaces, application programs, and the like, and the modem processor primarily processes wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 601. In some embodiments, processor 601 and memory 602 may be implemented on the same chip, or they may be implemented separately on separate chips in some embodiments.

The processor 601 may be a general purpose processor such as a Central Processing Unit (CPU), digital signal processor, application specific integrated circuit, field programmable gate array or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, which may implement or perform the methods, steps and logic blocks disclosed in embodiments of the application. The general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method for generating a room layout disclosed in connection with the embodiments of the present application may be directly embodied as a hardware processor executing the method, or may be executed by a combination of hardware and software modules in the processor.

The memory 602 is a non-volatile computer readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs, and modules. The Memory 602 may include at least one type of storage medium, which may include, for example, flash Memory, hard disk, multimedia card, card Memory, random access Memory (Random Access Memory, RAM), static random access Memory (Static Random Access Memory, SRAM), programmable Read-Only Memory (Programmable Read Only Memory, PROM), read-Only Memory (ROM), charged erasable programmable Read-Only Memory (ELECTRICALLY ERASABLE PROGRAMMABLE READ-Only Memory, EEPROM), magnetic Memory, magnetic disk, optical disk, and the like. Memory 602 is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 602 in embodiments of the present application may also be circuitry or any other device capable of performing storage functions for storing program instructions and/or data.

By programming the processor 601, the code corresponding to the method of generating a room layout described in the previous embodiments may be solidified into a chip, thereby enabling the chip to perform the steps of the method of generating a room layout of the embodiment shown in fig. 2 at run-time. How to design and program the processor 601 is a well-known technique for those skilled in the art, and will not be described in detail herein.

Based on the same inventive concept, embodiments of the present application also provide a storage medium storing computer instructions that, when run on a computer, cause the computer to perform the method of generating a room layout discussed previously.

In some possible embodiments, aspects of the scene restoration method provided by the present application may also be implemented in the form of a program product comprising program code for causing the control apparatus to carry out the steps in the method of generating a room layout according to the various exemplary embodiments of the application as described in the present specification when the program product is run on a device.

It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims

1. A method for generating a room layout, characterized in that the method comprises:

The average network signal strength of each terminal is obtained at different time periods; wherein, the average network signal strength is the average value when the network signal of each terminal remains stable.

The average signal strength of each network is clustered to obtain N clusters; where N is an integer greater than 1.

K fixed terminals are identified from the N clusters; wherein the K fixed terminals belong to different clusters, and K is an integer greater than 0;

Label the K fixed terminals with room identifiers, and generate the first room layout map based on all the room identifiers.

2. The method as described in claim 1, characterized in that obtaining the average network signal strength of each terminal at different time periods includes:

Obtain the network signal strength values of each terminal at different time periods; wherein, the network signal strength values do not include the network signal strength values when a jump occurs in a stable state;

The average network signal strength of each terminal at different time periods is obtained based on the network signal strength value.

3. The method as described in claim 1, characterized in that, the step of clustering the average values of each network signal strength to obtain N clusters includes:

A corresponding feature vector is formed based on the average network strength of each terminal;

By using a clustering algorithm, each feature vector is clustered to obtain N clusters.

4. The method as described in claim 1, wherein determining K fixed terminals among the N clusters comprises:

J fixed terminals are identified from the N clusters;

The J fixed terminals are grouped into pairs, and a relationship matrix of the J fixed terminals is created based on the grouping results.

The maximum complete subgraph corresponding to the J fixed terminals is calculated using the relation matrix, and the K fixed terminals in the maximum complete subgraph are determined.

5. The method as described in claim 1, characterized in that, after labeling the K fixed terminals with room identifiers and generating a first room layout diagram based on all the room identifiers, it further includes:

Obtain the cluster identifiers of the K fixed terminals and the cluster identifiers of the mobile terminals;

Determine whether the cluster identifier of the mobile terminal is the same as any of the cluster identifiers of the K fixed terminals;

If not, then add room labels to the first room layout diagram to generate a second room layout diagram.

6. An apparatus for generating a room layout, characterized in that the apparatus comprises:

The acquisition module is used to acquire the average network signal strength of each terminal at different time periods;

The processing module is used to cluster the average values of the network signal strengths to obtain N clusters;

The determination module is used to identify K fixed terminals among the N clusters;

The generation module is used to label room identifiers on K fixed terminals and generate a first room layout diagram based on all room identifiers.

7. The apparatus as described in claim 6, wherein the acquisition module is specifically used for:

Obtain the network signal strength values of each terminal at various time periods; wherein, the network signal strength values do not include network signal strength values that change during a stable state;

8. The apparatus of claim 6, wherein the processing module is specifically used for:

9. The apparatus of claim 6, wherein the determining module is specifically used for:

J fixed terminals are identified from the N clusters;

10. The apparatus of claim 6, wherein the generating module is further configured to:

11. An electronic device, characterized in that it comprises:

Memory, used to store computer programs;

A processor, when executing a computer program stored in the memory, implements the method steps of any one of claims 1-5.

12. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1-5.