CN113114547B - Statistical classification method, system and storage medium for home networking equipment - Google Patents
Statistical classification method, system and storage medium for home networking equipment Download PDFInfo
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- CN113114547B CN113114547B CN202110412829.2A CN202110412829A CN113114547B CN 113114547 B CN113114547 B CN 113114547B CN 202110412829 A CN202110412829 A CN 202110412829A CN 113114547 B CN113114547 B CN 113114547B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/2803—Home automation networks
- H04L12/2807—Exchanging configuration information on appliance services in a home automation network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/2803—Home automation networks
- H04L12/2823—Reporting information sensed by appliance or service execution status of appliance services in a home automation network
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention discloses a statistical classification method, a statistical classification system and a storage medium for home networking equipment, wherein the method comprises the following steps: screening the maximum distance value and the minimum distance value between each networking device and the home router from the distance data set, and calculating the difference value between the maximum distance value and the minimum distance value; calculating the ratio of the connection days of each networking device to the total days of the second statistical cycle one by one; and defining the networking equipment as the family fixed networking equipment, the family mobile networking equipment or the non-family mobile networking equipment according to the ratio and the difference. The method provided by the invention can be used for knowing which devices are fixed and which devices are frequently changed in position, which devices belong to family members and which devices belong to guests; by combining user names, hobbies and the like, the effects of statistical classification of networking equipment and construction of family relation network big data can be accurately carried out; the method has great benefits for future applications such as intelligent home control, advertisement putting, program recommendation, big data use and the like.
Description
Technical Field
The invention relates to the technical field of statistical classification methods of networking equipment, in particular to a statistical classification method, a statistical classification system and a storage medium of home networking equipment.
Background
Networking, in information technology, refers to the construction, design, and use of networks, including the physical (cables, hubs, bridges, switches, routers, etc.), the selection and use of communication protocols and computer software to use and manage the networks, and the establishment of mechanisms and procedures for the operation of the networks.
The networking device is a device using a network, and is mainly used for smart homes such as smart televisions and smart refrigerators, mobile phones, tablets, personal computers and the like.
Most of households generally include smart televisions, mobile phones, tablets and personal computers, which are all networking devices, but are not completely the same in application due to differences in portability, application installation convenience, application installation types and the like. Meanwhile, for a family unit, networking devices which do not belong to the family, such as mobile phones of guests and the like, are often mixed; if various networking devices appearing in a home can be accurately and statistically classified, great benefits are provided for the construction and use of advertisement placement, program recommendation, application recommendation, big data construction of a family relationship network, and the like, but at present, the prior art does not have the capability of accurate statistical classification, such as the prior art closest to the target:
the invention patent application with application publication number CN112311612A discloses a family portrait construction method (system architecture is shown in fig. 1), which includes the steps: 1. acquiring a first user log collected by a plurality of service systems, wherein the first user log carries a router identifier, a user identity identifier and position information; 2. identifying a home router identification from router identifications collected by the plurality of traffic systems based on the location information; 3. generating connection state information according to a second user log corresponding to the home router identification, and screening a plurality of user identification identifications associated with the home router identification according to the connection state information to determine home user identification; 4. and extracting user characteristics from a third user log corresponding to the home user identity identification, and generating a home portrait corresponding to the home router identification according to the user characteristics.
The family portrait construction method focuses on identifying a family router identifier, then screening and determining a family user identity identifier, and then generating a family portrait by extracting user characteristics; it is obvious that the patent application only counts the networking devices belonging to the home unit, does not classify the networking devices, does not count the networking devices not belonging to the home unit, and only excludes them.
In addition, the invention patent application with application publication number CN111163490A discloses a method for analyzing household residents based on mobile phone MAC, which comprises the following steps:
(1) equipment deployment: deploying equipment based on the stationing principle of the cell scene and the stationing principle of the building scene;
(2) data acquisition: connecting the equipment in the step (1) in a wired or wireless mode to acquire the volume data in the cell;
(3) data processing: data processing is carried out based on a python language so as to ensure the stability, expandability and fault tolerance of the data;
(4) and (3) data analysis: based on the collected data content, performing mobile phone mac data analysis on data which influence the judgment of the population number of the family residents due to the fact that the mobile phone mac addresses change continuously and data which do not change the mobile phone mac addresses, and outputting the final mobile phone mac number and the type of the residential community;
(5) application analysis: and performing visual application analysis based on the mac data, processing the mobile phone to generate a plurality of accompanying macs, and analyzing the user population and the household type based on the mac data source of a certain user.
The purpose of the patent application of the invention is to analyze whether residents in a cell reside in a short period of time, work or group residents so as to master the types of the residents in the cell and the family population in real time and improve the comprehensive treatment level of the security of the cell.
Thus, the prior art does not have the ability to statistically classify the networked devices that are present in a home accurately.
It can be seen that the prior art is still in need of improvement and development.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, it is an object of the present invention to provide a method, system and storage medium for statistical classification of home networking devices, which solve the problem that the prior art does not have the capability of performing accurate statistical classification of networking devices appearing in a home.
The technical scheme of the invention is as follows:
a method of statistical classification of home networking devices, comprising:
presetting a first statistical period for counting the distance data of the equipment and a second statistical period for counting the connection data of the equipment in the first statistical period;
acquiring all networking devices connected with the home router in the first statistical period, and respectively counting a distance data set between each networking device and the home router in the first statistical period and the number of days for connecting each networking device and the home router in the second statistical period;
screening the maximum distance value and the minimum distance value between each networking device and the home router from the distance data set, and calculating the difference value between the maximum distance value and the minimum distance value; calculating the ratio of the connection days of each networking device to the total days of the second statistical period one by one;
defining the networking equipment with the difference value less than or equal to a first threshold value and the ratio value greater than or equal to a second threshold value as the household fixed networking equipment; defining the networking equipment with the difference value larger than a first threshold value and the ratio value larger than or equal to a second threshold value as the home mobile networking equipment; and defining the networking equipment with the difference value larger than the first threshold value and the ratio value smaller than the second threshold value as the non-home mobile networking equipment.
The effect of above-mentioned scheme lies in: the home router can acquire which devices are connected with a home network, and then respectively calculate the distance fluctuation between each networking device and the home router and the ratio of the connection days to the total statistics days, so that the devices can be known to be fixed (movable, but generally unchanged in position), the positions of the devices are changed frequently, the devices belong to family members, and the devices belong to guests. In addition, the user name, hobbies (user portrait) and the like can be obtained from application program use information and the like on the networking equipment, so that the effects of accurately carrying out statistics and classification on the networking equipment and constructing big data of a family relationship network are achieved; the method has great benefits for future applications such as intelligent home control, advertisement putting, program recommendation, big data use and the like.
In a further preferred scheme, the maximum distance value and the minimum distance value between each networking device and the home router are screened from the distance data set, and a difference value between the maximum distance value and the minimum distance value is calculated; and the step of calculating the ratio of the number of connection days of each networked device to the total number of days of the second statistical period one by one further comprises: defining the networking equipment with the difference value larger than a first threshold value and the ratio value smaller than a second threshold value but larger than or equal to a third threshold value as the close-relation non-family mobile networking equipment; and defining the networking equipment with the difference value larger than the first threshold value and the ratio value smaller than the third threshold value as the common-relationship non-family mobile networking equipment.
The effect of above-mentioned scheme lies in: in the prior art, networking equipment of non-family members is directly excluded, and a family relation network is not constructed; according to the invention, not only are the networking devices of the non-family members included in the family relationship network, but also the networking devices of the non-family members classify the relationship between a certain person and the counted family into the close relationship and the common relationship by setting the third threshold, so that the construction of the interpersonal relationship network is finely divided, and the accuracy of constructing big data of the family relationship network is improved.
In a further preferred scheme, the networking device with the difference value larger than the first threshold value and the ratio value smaller than the second threshold value but larger than or equal to the third threshold value is defined as an intimate non-home mobile networking device; the step of defining the networked devices having a difference greater than the first threshold and a ratio less than the third threshold as normal relationship non-home mobile networked devices further comprises: and determining whether a plurality of non-home mobile networking devices which are simultaneously connected with the home router have a plurality of non-home mobile networking devices belonging to one home or not according to the connection time of the non-home mobile networking devices and the home router, so as to construct a home-personal relationship network, a home-home relationship network or a home-personal relationship network.
The effect of above-mentioned scheme lies in: if a plurality of non-family mobile networking devices are connected with the family router at the same time, and two or more non-family mobile networking devices belong to one family, the relationship between the two families is shown, and according to the fact that the non-family mobile networking devices are close-relationship non-family mobile networking devices or common-relationship non-family mobile networking devices, the relationship classification between the two families can be determined, so that a more accurate family relationship network can be constructed; if a plurality of non-family mobile networking devices are connected with the family router at the same time and all the non-family mobile networking devices do not belong to the same family, the situation that the family is related to the user individual of the corresponding mobile networking device but not the family is shown, and therefore a more accurate family relation network can be determined; if both conditions exist, a family-personal relationship network with the counted family as the core is established.
In a further preferred scheme, a family of initial statistics is set as a first family, and another family in a family-family relationship network or a family-personal relationship network constructed by taking the first family as a core is set as a second family, the family-family relationship network and the family-personal relationship network are respectively a first family-second family relationship network and a first family-second family-personal relationship network, a family mobile networking device of the first family is a first family mobile networking device, and a family router of the second family is a third family router;
the step of determining whether a plurality of non-home mobile networking devices connected with the home router simultaneously belong to a home or not according to the connection time of the non-home mobile networking devices and the home router so as to construct a home-personal relationship network, a home-home relationship network or a home-personal relationship network further comprises the following steps: and tracking the router belonging to the third family according to the non-family mobile networking equipment, counting the connection number and the connection days of the first family mobile networking equipment and the third family router, and re-determining the relationship intimacy between the first family and the second family.
The effect of above-mentioned scheme lies in: the relation accuracy between families is judged to be insufficient only according to a one-way statistical result; according to the invention, through a reverse tracking statistical mode, the relationship network between families is constructed by combining the data of the two families from the beginning to the end (the data of the two family routers respectively connected with the mobile networking devices of the two families), so that the accuracy is higher, and the construction of the relationship network is more comprehensive.
In a further preferred scheme, the distance between the networking device and the home router is calculated by the formula: lgD ═ (Los-32.44-20 × lgF)/20; los is the propagation loss of the signal, F is the operating frequency of the router, and D is the distance between the networking device and the router.
The effect of above-mentioned scheme lies in: according to the principle that radio waves or sound waves are transmitted in a medium, the power of a signal is attenuated with the propagation distance. The distance between the nodes can be calculated through an attenuation model between the signals and the distance according to the transmitting power of the known signals of the beacon nodes and the power of the signals received by the nodes. Because the finally needed data of the invention is the difference value between the maximum distance value and the minimum distance value between the networking equipment and the home router, the calculation result does not require higher accuracy, namely the invention reduces the dependence on the accuracy of the attenuation model and improves the judgment efficiency of the properties of the networking equipment.
In a further preferred embodiment, the step of acquiring all the networking devices connected to the home router in the first statistical period, and separately counting a distance data set between each networking device and the home router in the first statistical period, and the number of days each networking device is connected to the home router in the second statistical period further includes: and scanning the information of the devices connected to the home router every half hour, recording the scanning time, and determining all networking devices which have access to the home router by combining a probe technology.
The effect of above-mentioned scheme lies in: the WiFi probe technology is to identify a smartphone or a WiFi terminal (a notebook, a tablet, etc.) that has turned on WiFi near an AP (wireless access point) based on a WiFi detection technology, and the WiFi probe can identify information of a user without accessing the WiFi by the user. When a user walks into the probe signal coverage area and the wifi device is opened, the device can be detected by the probe, whether the IOS or the android system can easily detect the device, and the MAC address of the device is obtained. The invention utilizes the probe technology to combine with the equipment information of the timing scanning access home router, and comprises three aspects: 1. all networking equipment in the WiFi coverage range can be scanned by utilizing a probe technology, so that the comprehensiveness of statistical classification can be improved; 2. the device information of the home router is scanned and accessed in a timing mode, and the noise scanned by the probe technology can be removed (although some networking device or certain networking devices are in the WiFi coverage range, the home router is never accessed, and the noise is obtained); 3. the accuracy of equipment classification can be improved by combining the probe technology and the timing scanning, for example, a certain household has two mobile phones, one is frequently used, one is occasionally connected with a household router (for example, the mobile phone is basically only used for navigation), if the timing scanning technology is only used, the latter is easily judged to be a non-household networking equipment (the equipment is mistakenly judged as a guest because the equipment is basically only used for navigation and has no user information), but the probe technology is combined, the days of the latter which is not connected with WiFi but is in a coverage range can also be counted into the connection days, so that the accuracy of equipment statistical classification can be improved.
In a further preferred embodiment, the step of acquiring all networking devices connected to the home router in the first statistical period specifically includes: and judging whether the router is a home router, if so, continuously judging whether the home of the home router has other home routers, and if so, acquiring all networking equipment connected with all home routers in the first statistical period.
The effect of above-mentioned scheme lies in: the invention collects all the networking equipment information of the whole family by judging whether one family has a plurality of family routers, thereby ensuring that the comprehensiveness of the statistical classification result is not insufficient due to missing family members or the networking equipment of the family members.
In a further preferred embodiment, if it is determined that the router is a home router, continuing whether there are other home routers in the home to which the home router belongs specifically includes:
setting an initial home router as a first home router, acquiring a home mobile networking device list under the first home router, and acquiring a router list connected with each home mobile networking device one by one;
and judging whether the routers in the router list are the home routers one by one and belong to the same home as the first home router.
The effect of above-mentioned scheme lies in: the list of home mobile networking devices has two meanings: 1. mobile networking equipment (such as a mobile phone, a tablet, a notebook computer and the like) connected with the first home router cannot be omitted, so that the comprehensiveness is ensured; 2. the first home router and the home router belong to the same home, and deviation of statistical classification of home networking equipment due to the fact that mobile networking equipment which does not belong to the home is mixed in the first home router and the home networking equipment. The router list connected with each family mobile networking device is acquired one by one, and then the first family router is judged to belong to the same family, so that the effects can be achieved: 1. in the judging process, all routers connected with the home mobile networking equipment cannot be omitted, and comprehensiveness is guaranteed; 2. and the routers which do not belong to the family are screened out, and the accuracy of statistical classification of the family networking equipment is ensured.
In a further preferred embodiment, if it is determined that the router is a home router, continuing whether there are other home routers in the home to which the home router belongs further includes:
setting an initial home router as a first home router, acquiring a home mobile networking device list under the first home router, and acquiring a router list connected with each home mobile networking device one by one;
and determining whether the family has a private vacation house according to the connection frequency and the connection days of the mobile networking equipment and the routers in the router list and the distance between the routers in the router list and the family router, and statistically classifying the family networking equipment.
The effect of above-mentioned scheme lies in: the special vacation house is a house which belongs to the family and is specially used for vacation, and has two characteristics: 1. no non-home mobile networking device is connected to the corresponding home router; 2. the frequency of occupancy is relatively low (the corresponding home router usage frequency is relatively low); it is clear that the exclusive vacation home belongs to the home, and in case the exclusive vacation home has a fixed networking device (such as a television, a home projector, etc.), the comprehensiveness of the statistical classification of the home networking device of the exclusive vacation home is insufficient.
A system for implementing a method for statistical classification of home networking devices, comprising a memory for storing a home networking device statistical classification program and a processor for running the home networking device statistical classification program to implement the method as described above. The system comprises all technical characteristics of the household networking equipment statistical classification method, so that the system also has all technical effects of the household networking equipment statistical classification method, and is not repeated.
A storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the method for statistical classification of home networking devices as described above. The storage medium comprises all technical characteristics of the household networking equipment statistical classification method, so that all technical effects of the household networking equipment statistical classification method are achieved, and the description is omitted.
Compared with the prior art, the statistical classification method for the home networking equipment, provided by the invention, comprises the following steps: respectively counting a distance data set between each networking device and the home router in a first counting period and the number of days for connecting each networking device and the home router in a second counting period; screening the maximum distance value and the minimum distance value between each networking device and the home router from the distance data set, and calculating the difference value between the maximum distance value and the minimum distance value; calculating the ratio of the connection days of each networking device to the total days of the second statistical period one by one; defining the networking equipment with the difference value less than or equal to a first threshold value and the ratio value greater than or equal to a second threshold value as the household fixed networking equipment; defining the networking equipment with the difference value larger than a first threshold value and the ratio value larger than or equal to a second threshold value as the home mobile networking equipment; and defining the networking equipment with the difference value larger than the first threshold value and the ratio value smaller than the second threshold value as the non-home mobile networking equipment. The method provided by the invention can acquire which devices are connected with the home network through the home router, and then respectively calculate the distance fluctuation between each networking device and the home router and the ratio of the connection days to the total statistics days, so that the method can acquire which devices are fixed (can move but the positions of the devices are not changed usually), which devices are changed frequently, which devices belong to family members and which devices belong to guests. In addition, the user name, hobbies (user portrait) and the like can be obtained from application program use information and the like on the networking equipment, so that the effects of accurately carrying out statistics and classification on the networking equipment and constructing big data of a family relationship network are achieved; the method has great benefits for future applications such as intelligent home control, advertisement putting, program recommendation, big data use and the like.
Drawings
Fig. 1 is a flow chart of a statistical classification method for home networking devices according to the present invention.
Detailed Description
The invention provides a method, a system and a storage medium for statistical classification of home networking equipment, and in order to make the purpose, technical scheme and effect of the invention clearer and clearer, the invention is further described in detail below by referring to the attached drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as operated herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present invention. The word "if" as run herein may be interpreted as "at … …" or "at … …" or "in response to a determination", depending on the context.
The noun explains:
networking equipment: refers to devices using a network, such as: smart homes (smart televisions, smart refrigerators, smart door locks, smart lighting systems, smart voice devices, etc.), cell phones, tablets, desktop computers, notebook computers, and the like.
A first statistical period: the time period is a specific time period for counting the distance between the networking device and the home router, and may be, for example, 1 month, 3 months, and the like, and the specific time period is not limited.
And a second statistical period: the time period is a specific time period for counting information of networking devices connected to the home router, and in a first statistical period, for example, the first statistical period is 1 month, the second statistical period may be 8 pm later to 10 pm earlier per day in the 1 month.
The home router: the router belonging to the family unit does not refer to a certain router.
Distance data set: refers to the collection of all distances between each networked device and the home router collected during the first statistical period.
Days of ligation: refers to the number of days of cumulative connection between the networking device (only for mobile networking devices such as cell phones, tablets) and the home router during the second statistical period.
Fixed networking equipment of family: refers to networked devices (such as intelligent refrigerators, intelligent televisions, etc.) belonging to a counted household that are typically not moving.
Home mobile networking device: the device refers to a networking device (such as a mobile phone, a tablet and the like) belonging to a counted family and having a large distance fluctuation value with a family router.
Non-home mobile networking device: the device is a networking device (such as a mobile phone and a tablet of a guest) which does not belong to the counted family and has a large distance fluctuation value with a family router.
The invention provides a statistical classification method for home networking equipment, which comprises the following steps:
s100, presetting a first statistical period for counting the distance data of the equipment and a second statistical period for counting the connection data of the equipment in the first statistical period.
It should be noted that the first statistical period and the second statistical period do not need to be preset in the system, and after data is collected for a certain period of time, an operator may filter the data for a certain period of time to perform statistical analysis, for example, after data is continuously collected for 3 months, the collected distance information is counted, and the collected connection time data is filtered for a certain period of time every day. Of course, it is also possible to collect data only for a specific time period by setting a timer in the system.
S200, acquiring all the networking devices connected with the home router in the first statistical period, and respectively counting a distance data set between each networking device and the home router in the first statistical period and the number of days for which each networking device is connected with the home router in the second statistical period.
In particular, the data acquisition can be realized by the following modes: and scanning the information of the devices connected to the home router every half hour, recording the scanning time, and determining all networking devices which have access to the home router by combining a probe technology.
That is, the invention preferably scans and records the equipment information connected on the home router once every half hour, and correspondingly records the scanning time; meanwhile, during scanning, recording all networking equipment information in all WiFi coverage ranges by using a probe technology; during statistics, deleting the information of the networking equipment which is detected by the probe technology but is not connected with the home router, and not analyzing; the networking device information that was connected to the home router is based on the data detected by the probe technology (for example, if a certain mobile terminal is connected to the home router twice, which is distributed in 2 days, and the number of connection days is 2 days in the normal statistical manner, but if the number of times of detecting the mobile terminal is 300 times, which is distributed in 50 days, which is distributed in the statistical manner of the present invention, the number of connection days is 50 days).
In addition, the timing scanning and probe technology can also be used to remove noise in conjunction with user images (for example, if a certain mobile terminal is connected to a home router twice, and is distributed in 2 days, and the number of connection days is 2 days according to a common statistical manner, if the number of times the mobile terminal is detected to be 300 times according to the probe technology and is distributed in 50 days, then the number of connection days is 50 days according to the statistical manner of the probe technology, but it is known from the user image that the user corresponding to the mobile terminal is not a member of the home, and according to a further preferred embodiment of the present invention, it can be determined that the user is a neighbor of the home, and should be included in a home relationship network, but not a member of the home). The user portrait construction is the prior art, has various implementation schemes, and the invention only combines the user portrait construction into the statistical classification method of the home networking equipment, and does not specifically limit the specific implementation mode.
Preferably, the distance between the networking device and the home router is calculated by the formula: lgD ═ (Los-32.44-20 × lgF)/20; where Los is the propagation loss of the signal (in dB), F is the operating frequency of the router (in MHz), and D is the distance between the networking device and the router (in Km).
RSSI is a theoretical term for radio frequency signals and is mainly applied to distance measurement between a transmitter and a receiver. The method determines the distance according to the energy intensity of the received signal, and has higher requirements on communication channel parameters. The distance measurement theory is as follows: in terms of the transmission of radio or acoustic waves in a medium, the signal power is a principle of attenuation with propagation distance. The distance between the nodes can be calculated through an attenuation model between the signals and the distance according to the transmitting power of the known signals of the beacon nodes and the power of the signals received by the nodes.
That is to say, the invention can calculate the distance between the networking device and the home router according to the formula only by acquiring the strength of the signal received by the networking device.
The data preferably stored by the present invention includes: the home device location data and the home device connection data are specifically as follows:
home device location data:
| field(s) | Type (B) | Note | Description of the invention |
| SSID | Character string | Wireless name of wireless network | |
| RSSI | Character string | Strength and weakness of signal | |
| WiFi_MAC | Character string | Router MAC | Using the ID as the ID of the family |
| MAC | Character string | Networking device MAC | Containing all devices to be sorted |
| F | Numerical value | Router operating frequency | |
| Date | Date | Time of scan |
Home device connection data:
s300, screening the maximum distance value and the minimum distance value between each networking device and the home router from the distance data set, and calculating the difference value between the maximum distance value and the minimum distance value; and calculates the ratio of the number of connection days of each networked device to the total number of days of the second statistical period one by one.
S400, defining the networking equipment with the difference value less than or equal to a first threshold value and the ratio value greater than or equal to a second threshold value as the household fixed networking equipment; defining the networking equipment with the difference value larger than a first threshold value and the ratio value larger than or equal to a second threshold value as the home mobile networking equipment; and defining the networking equipment with the difference value larger than the first threshold value and the ratio value smaller than the second threshold value as the non-home mobile networking equipment.
The first threshold may be set to 1m, and the second threshold may be set to 50%, although the present invention is not limited thereto.
As a preferred embodiment of the present invention, the step S300 further includes the following steps: defining the networking equipment with the difference value larger than a first threshold value and the ratio value smaller than a second threshold value but larger than or equal to a third threshold value as the close-relation non-family mobile networking equipment; and defining the networking equipment with the difference value larger than the first threshold value and the ratio value smaller than the third threshold value as the common-relationship non-family mobile networking equipment.
The third threshold may be set to 10%, assuming that the first threshold is 1m, the second threshold is 50%, and the third threshold is 10%, the non-home mobile networking device may be further divided into: intimate non-home mobile networking equipment (the equipment ratio is less than 50% and greater than or equal to 10%) and ordinary relational non-home mobile networking equipment (the equipment ratio is less than 10%). It is to be understood that the specific values recited herein are exemplary only and are not intended to limit the scope of the invention. In addition, on the basis of the present invention, the non-home mobile networking device may be further divided into more detailed categories, which is not specifically limited by the present invention.
Further, after S400, the method further includes: and determining whether a plurality of non-home mobile networking devices which are simultaneously connected with the home router belong to a plurality of non-home mobile networking devices of a home or not according to the connection time of the non-home mobile networking devices and the home router, so as to construct a home-personal relationship network, a home-home relationship network or a home-personal relationship network.
For example, a scanning result at a certain time point relates to 5 non-home mobile networking devices which are connected with a home router (belonging to a home X) and respectively belong to a user A, a user B, a user C, a user D and a user E, and if the users A to E do not belong to the same home, the invention can construct a home X-personal (A-E) relationship network by taking the home X as a core; if the users A, B and C belong to the family Y and the users C and D belong to the family Z, the family Y-family X-family Z relationship network can be constructed by taking the family X as a core; if the users A, B and C belong to the same family Y, and the users C and D do not belong to the same family, the invention can construct a family Y-family X-user D, E relation network by taking the family X as a core.
Further, if the constructed relationship network relates to another family, the invention also adopts a reverse statistical method to combine the data of the two families by analyzing the data of the networked devices of the second family (such as the family Y and the family Z in the above example) to construct a more accurate relationship network. Such as: the family Y passes through the family X twice within 3 months, and if the third threshold is 10%, the relationship between the family X and the family Y is defined as a common relationship; however, through inverse statistics, when family X comes 10 times in the same period, the two terms are added up to be 12 times, the ratio is about 13%, and is greater than the third threshold, the relationship between family X and family Y should be defined as close relationship. Obviously, the statistical classification result after reverse statistics is more accurate.
According to another aspect of the present invention, the step of acquiring all networking devices connected to the home router in the first statistical period is specifically: and judging whether the router is a home router, if so, continuously judging whether other home routers exist in the home to which the home router belongs, and if so, acquiring all networking equipment connected with all home routers in the first statistical period.
There are many ways to determine whether the router is a home router, which are exemplary: the weighting processing can be carried out according to the connection information of the mobile phones in different time periods, and meanwhile, the number of the connected mobile phone devices, the name, the longitude and latitude, and the POI (Point of interest, namely, any non-geographic meaningful Point on a map, such as a shop, a bar, a gas station, a hospital, a station and the like, are added, and the comprehensive judgment of information, such as a city, a river, a mountain and the like, which does not belong to the POI, is a geographic coordinate.
The latitude and longitude information is obtained exemplarily as follows: and acquiring longitude and latitude information (preferably, the longitude and latitude information is accurate to 6 digits after decimal point) according to the MAC.
The following table shows the accuracy and error of longitude and latitude, and the accuracy of the longitude and latitude of the router is preferably 0.000001, so the positioning accuracy is higher, and the deviation is about 0.11:
| equatorial circumference (Rice) | Degree (degree) |
| 40076000 | 360 |
| 111322.2222 | 1 |
| 11132.22222 | 0.1 |
| 1113.222222 | 0.01 |
| 111.3222222 | 0.001 |
| 11.32222222 | 0.0001 |
| 1.113222222 | 0.00001 |
| 0.111322222 | 0.000001 |
| 0.011132222 | 0.0000001 |
In addition, the longitude and latitude information can be analyzed through the frequency of the IP address of the mobile networking equipment to determine the geographic position of the family (other modes are not listed one by one); similarly, the prior art may be referred to for determining whether the router is a home router, and the present invention is not limited in particular.
In the preferred embodiment of the present invention, determining whether a router and a first home router belong to the same home mainly proceeds from two aspects: 1. whether the degree of overlap between the router and the mobile networking device connected to the first home router exceeds a certain threshold (e.g., 50%, a non-specific numerical value, for example only); 2. whether the distance between the router and the first home router is less than a certain threshold (e.g., 10 meters, a non-specific limiting value, for example only); of course, more elements may be added for determination, and the invention also belongs to the protection scope.
If the router is judged to be the home router, whether other home routers exist in the family to which the home router belongs or not is continued to specifically comprise:
setting an initial home router as a first home router, acquiring a home mobile networking device list under the first home router, and acquiring a router list connected with each home mobile networking device one by one.
Specifically, a list of mobile networking devices under the first home router may be obtained (i.e., which mobile networking devices the first home router has connected to may be collected), and then, according to information such as connection frequency and connection duration, which mobile networking devices belong to the home may be determined (non-home mobile networking devices such as guest temporary connection information are screened); of course, the method for determining the home mobile networking device list is not specifically limited in the present invention, and those skilled in the art can also refer to the prior art to achieve the purpose, and the manner for obtaining the home mobile networking device list is only an example.
And judging whether the routers in the router list are the home routers one by one and belong to the same home as the first home router. The manner of determining whether the router is the home router may refer to the above description, and determining whether the router and the first home router belong to the same home may be determined by the overlap ratio of the mobile networking devices, the distance between the two, and other factors.
As a further preferred embodiment of the present invention, information on whether a target family has multiple properties may also be obtained, for example, a certain family has two properties, one is in a permanent residence and one is used for vacation, by using the technical means of the present invention for obtaining all home network devices belonging to the same family, according to the overlapping degree of mobile networking devices and the time proximity of multiple mobile networking devices [ for example, a certain family has 4 members, except for a first home network device, a suspected second home network device (the overlapping degree of the mobile networking devices of the home network device is extremely high but far away), when the 4 home members are often connected to the suspected second home network device at the same time, and the suspected second home network device is basically not connected to the mobile networking device at the rest time, it may be determined that the family has two properties ].
A system for implementing a method for statistical classification of home networking devices, comprising a memory for storing a home networking device statistical classification program and a processor for running the home networking device statistical classification program to implement the method as described above. The system comprises all technical characteristics of the household networking equipment statistical classification method, so that the system also has all technical effects of the household networking equipment statistical classification method, and is not repeated.
A storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the method for statistical classification of home networking devices as described above. The storage medium comprises all technical characteristics of the household networking equipment statistical classification method, so that all technical effects of the household networking equipment statistical classification method are achieved, and the description is omitted.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), synchronous Link (SyNchlinNk) DRAM (SLDRAM), Rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (9)
1. A method for statistical classification of home networking devices, comprising:
presetting a first statistical period for counting the distance data of the equipment and a second statistical period for counting the connection data of the equipment in the first statistical period;
acquiring all networking devices connected with the home router in the first statistical period, and respectively counting a distance data set between each networking device and the home router in the first statistical period and the number of days for connecting each networking device and the home router in the second statistical period;
screening the maximum distance value and the minimum distance value between each networking device and the home router from the distance data set, and calculating the difference value between the maximum distance value and the minimum distance value; calculating the ratio of the connection days of each networking device to the total days of the second statistical period one by one;
defining the networking equipment with the difference value less than or equal to a first threshold value and the ratio value greater than or equal to a second threshold value as the household fixed networking equipment; defining the networking equipment with the difference value larger than a first threshold value and the ratio value larger than or equal to a second threshold value as the household mobile networking equipment; defining the networking equipment with the difference value larger than a first threshold value and the ratio value smaller than a second threshold value as non-family mobile networking equipment;
the step of acquiring all networking devices connected with the home router in the first statistical period specifically includes: judging whether the router is a home router or not, if so, continuously judging whether the home of the home router has other home routers;
if the router is judged to be the home router, continuously judging whether the home to which the home router belongs has other home routers specifically further comprises:
setting an initial home router as a first home router, acquiring a home mobile networking device list under the first home router, and acquiring a router list connected with each home mobile networking device one by one;
and determining whether the family has a private vacation house according to the connection frequency and the connection days of the household mobile networking equipment and the router in the router list and the distance between the router in the router list and the first household router, and statistically classifying the household networking equipment.
2. The method according to claim 1, wherein the distance data set is filtered to obtain a maximum distance value and a minimum distance value between each networking device and the home router, and a difference between the maximum distance value and the minimum distance value is calculated; and the step of calculating the ratio of the number of connection days of each networked device to the total number of days of the second statistical period one by one further comprises: defining the networking equipment of which the difference value is greater than a first threshold value, and the ratio is less than a second threshold value but greater than or equal to a third threshold value as the intimate relationship non-family mobile networking equipment; and defining the networking equipment with the difference value larger than the first threshold value and the ratio value smaller than the third threshold value as the common-relationship non-family mobile networking equipment.
3. The method of statistical classification of home networking devices according to claim 2, wherein networking devices having a difference greater than a first threshold and a ratio less than a second threshold but greater than or equal to a third threshold are defined as close-coupled non-home mobile networking devices; the step of defining the networked devices having a difference greater than the first threshold and a ratio less than the third threshold as normal relationship non-home mobile networked devices further comprises: and determining whether a plurality of non-home mobile networking devices which are simultaneously connected with the home router have a plurality of non-home mobile networking devices belonging to one home or not according to the connection time of the non-home mobile networking devices and the home router, so as to construct a home-personal relationship network, a home-home relationship network or a home-personal relationship network.
4. The method of statistical classification of home networking devices according to claim 3, wherein the distance between the networking device and the home router is calculated by the formula: lgD = (Los-32.44-20 × lgF)/20; los is the propagation loss of the signal, F is the operating frequency of the router, and D is the distance between the networking device and the router.
5. The method for statistical classification of home networking devices according to claim 4, wherein the step of obtaining all networking devices connected to the home router in the first statistical period and separately counting the distance data set between each networking device and the home router in the first statistical period and the number of days each networking device is connected to the home router in the second statistical period further comprises: and scanning the information of the devices connected to the home router every half hour, recording the scanning time, and determining all networking devices which have access to the home router by combining a probe technology.
6. The method for statistically classifying home networking devices according to claim 5, wherein the step of determining whether the router is a home router, and if so, continuing to determine whether the home to which the home router belongs has other home routers further comprises: and if so, acquiring all networking equipment connected with all home routers in the first statistical period.
7. The method of claim 6, wherein if the router is determined to be a home router, the step of continuing whether the home to which the home router belongs has other home routers specifically comprises:
setting an initial home router as a first home router, acquiring a home mobile networking device list under the first home router, and acquiring a router list connected with each home mobile networking device one by one;
and judging whether the routers in the router list are the home routers one by one and belong to the same home as the first home router.
8. A system for implementing a method for statistical classification of home networking devices, comprising a memory for storing a home networking device statistical classification program and a processor for operating the home networking device statistical classification program to implement the method for statistical classification of home networking devices as claimed in any one of claims 1 to 7.
9. A storage medium having stored thereon a computer program, characterized in that the computer program, when being executed by a processor, realizes the steps of the method for statistical classification of home networking devices according to any one of claims 1 to 7.
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