User schedule list generation method, analysis method, device, equipment and medium

Abstract

The present application is suitable for the field of information processing, and particularly relates to a user work and rest list generation method and analysis method, device, equipment and medium. The present application collects the start broadcast information and the first wireless signal of the user fixed device, the first wireless signal of the user mobile device, the second wireless signal between the user fixed device and the user mobile device and the collection time when the user fixed device and the user mobile device are in the same local area network, calculates the first wireless signal difference between the first wireless signals, obtains the device distance information between the user fixed device and the user mobile device according to the first wireless signal difference, the second wireless signal and the preset distance mapping table, and sends the start broadcast information, the device distance information and the collection time to the server. The behavior information and the position information of the target user are represented by using the start broadcast information and the signal relationship between the user fixed device and the user mobile device, and the accuracy of the user work and rest list is improved.

Description

Technical Field

[0001] This invention relates to the field of information processing technology, and in particular to a method, analysis method, apparatus, equipment and medium for generating user schedules. Background Technology

[0002] With the rapid development of smart devices, users are increasingly focusing on tailoring specific services to their lifestyle habits. Given the widespread use of smart TVs and smartphones in daily life, current methods primarily involve statistically analyzing screen-on and screen-off times of smart TVs and smartphones to determine user behavior and generate a user's daily routine checklist. Based on this checklist, services can be intelligently tailored to better meet the user's needs.

[0003] However, the above methods focus on the screen-on and screen-off times of smart TVs and smartphones themselves, and cannot perform unified correlation analysis on smart TVs and smartphones, resulting in poor accuracy of the generated daily routine lists and failing to meet users' characteristic service needs.

[0004] Therefore, in the field of information processing technology, how to improve the accuracy of user schedule generation has become an urgent problem to be solved. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a method, analysis method, apparatus, device, and medium for generating user schedules, in order to solve the problem of low accuracy in generating user schedules at present.

[0006] In a first aspect, embodiments of the present invention provide a method for generating a user's schedule, the method comprising:

[0007] When the user fixed device and the target user's mobile device are on the same local area network, the broadcast start information and first wireless signal of the user fixed device, the first wireless signal of the user mobile device, the second wireless signal between the user fixed device and the user mobile device, and the corresponding collection time are collected.

[0008] Calculate the first wireless signal difference between the first wireless signal of the user fixed equipment and the first wireless signal of the user mobile device;

[0009] A preset distance mapping table is obtained. Based on the first wireless signal difference, the second wireless signal, and the distance mapping table, the device distance information between the user fixed device and the user mobile device is obtained. The distance mapping table is used to characterize the mapping relationship between the first wireless signal difference, the second wireless signal, and the device distance.

[0010] The broadcast start information, the device distance information, and the collection time are sent to the server. The server analyzes the broadcast start information, the device distance information, and the collection time to obtain the user's daily schedule list corresponding to the target user.

[0011] Secondly, embodiments of the present invention provide a method for analyzing user schedules, the analysis method comprising:

[0012] The system receives the collection time, the start-up information of the user's fixed device, and the device distance information between the user's fixed device and the user's mobile device from the target user. Based on the collection time and a preset time interval, the system divides the start-up information and the device distance information into N groups, where N is an integer greater than 0.

[0013] For any set of broadcast start information and device distance information, determine the location information of the user's mobile device based on the device distance information, and determine the user's daily routine behavior based on the broadcast start information and the location information;

[0014] By iterating through all the broadcast information and device distance information, N user daily routines are obtained, and the N user daily routines are arranged into a user daily routine list according to the order of their corresponding collection times.

[0015] Thirdly, embodiments of the present invention provide a device for generating a user's schedule, the device comprising:

[0016] The signal acquisition module is used to acquire, when the user fixed device and the target user's user mobile device are on the same local area network, the user fixed device's start-up information and first wireless signal, the user mobile device's first wireless signal, the second wireless signal between the user fixed device and the user mobile device, and the corresponding acquisition time.

[0017] The difference calculation module is used to calculate the first wireless signal difference between the first wireless signal of the user fixed equipment and the first wireless signal of the user mobile device.

[0018] The distance mapping module is used to obtain a preset distance mapping table, and to obtain the device distance information between the user fixed device and the user mobile device based on the first wireless signal difference, the second wireless signal and the distance mapping table. The distance mapping table is used to characterize the mapping relationship between the first wireless signal difference, the second wireless signal and the device distance.

[0019] The data sending module is used to send the start-up information, the device distance information, and the collection time to the server. The server is used to analyze the start-up information, the device distance information, and the collection time to obtain the user's schedule corresponding to the target user.

[0020] Fourthly, embodiments of the present invention provide an analysis device for a user's schedule, the analysis device comprising:

[0021] The data acquisition module is used to receive the collection time, the start-up information of the user's fixed device, and the device distance information between the user's fixed device and the user's mobile device of the target user, and to divide the start-up information and the device distance information into N groups according to the collection time and a preset time interval, where N is an integer greater than 0.

[0022] The activity and rest behavior determination module is used to determine the location information of the user's mobile device based on the device distance information for any set of the start-up information and the device distance information, and to determine the user's activity and rest behavior of the target user based on the start-up information and the location information.

[0023] The schedule determination module is used to traverse all the start-up information and the device distance information to obtain N user schedule behaviors, and to assemble the N user schedule behaviors into a user schedule list according to the order of their corresponding collection times.

[0024] Fifthly, embodiments of the present invention provide a computer device, the computer device including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for generating a user schedule as described in the first aspect.

[0025] In a sixth aspect, embodiments of the present invention provide a computer device, the computer device including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the user schedule analysis method as described in the second aspect.

[0026] In a seventh aspect, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for generating a user schedule as described in the first aspect.

[0027] Eighthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the user schedule analysis method as described in the second aspect.

[0028] The beneficial effects of Embodiment 2 of the present invention compared with the prior art are as follows: When the user's fixed device and the target user's mobile device are in the same local area network, the system collects the start-up information and first wireless signal of the user's fixed device, the first wireless signal of the user's mobile device, the second wireless signal between the user's fixed device and the user's mobile device, and the corresponding collection time. It calculates the first wireless signal difference between the first wireless signal of the user's fixed device and the first wireless signal of the user's mobile device. Based on the first wireless signal difference, the second wireless signal, and a preset distance mapping table, it obtains the device distance information between the user's fixed device and the user's mobile device. The start-up information, device distance information, and collection time are sent to the server. The start-up information and the signal relationship between the user's fixed device and the user's mobile device are used to characterize the target user's behavior information and location information, thereby improving the accuracy of the user's schedule.

[0029] The beneficial effects of Embodiment 3 of the present invention compared with the prior art are as follows: By receiving the collection time, the start-up information of the user's fixed device, and the device distance information between the user's fixed device and the user's mobile device sent by the target user, the start-up information and device distance information are divided into N groups according to the collection time and a preset time interval. For any group of start-up information and device distance information, the location information of the user's mobile device is determined according to the device distance information. Based on the start-up information and location information, the user's daily routine is determined. By traversing all the start-up information and device distance information, N user daily routines are obtained. The N user daily routines are arranged into a user daily routine list according to the order of the corresponding collection time. By combining different start-up information and different location information, different user daily routines of the target user are characterized, thereby improving the accuracy of user daily routine judgment. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a schematic diagram of an application environment for a method for generating and analyzing a user's schedule provided in Embodiment 1 of the present invention;

[0032] Figure 2 This is a flowchart illustrating a method for generating a user's schedule according to Embodiment 2 of the present invention;

[0033] Figure 3This is a flowchart illustrating a method for analyzing a user's daily schedule provided in Embodiment 3 of the present invention;

[0034] Figure 4 This is a schematic diagram of the structure of a user schedule generation device provided in Embodiment 4 of the present invention;

[0035] Figure 5 This is a schematic diagram of the structure of a user schedule analysis device provided in Embodiment 5 of the present invention;

[0036] Figure 6 This is a schematic diagram of the structure of a computer device provided in Embodiment Six of the present invention. Detailed Implementation

[0037] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0038] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0039] It should also be understood that the term “and / or” as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0040] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0041] Furthermore, in the description of this invention and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0042] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of the invention include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0043] It should be understood that the sequence number of each step in the following embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0044] To illustrate the technical solution of the present invention, specific embodiments are described below.

[0045] See Figure 1 This is the application environment provided in Embodiment 1 of the present invention, in which a user's fixed device communicates with the server. The user's fixed device includes, but is not limited to, the target user's smart TV, desktop computer, laptop computer, and other fixed devices. The server can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0046] See Figure 2 This is a flowchart illustrating a method for generating a user schedule according to Embodiment 2 of the present invention. The method for generating a user schedule can be applied to... Figure 1 For user-fixed devices, the method for generating the user's schedule may include the following steps:

[0047] Step S201: When the user's fixed device and the target user's mobile device are on the same local area network, collect the start-up information and first wireless signal of the user's fixed device, the first wireless signal of the user's mobile device, the second wireless signal between the user's fixed device and the user's mobile device, and the corresponding collection time.

[0048] Among them, the user's fixed equipment can be a smart TV used by the target user at their residence, the user's mobile device can be a smartphone carried by the target user, and the residence can be a home, dormitory or other daily living place.

[0049] When a target user's fixed device and mobile device are on the same local area network, it indicates that the target user is in their place of residence. Therefore, based on the signal relationship between the fixed device and the mobile device, the target user's movement information in their place of residence can be analyzed. Then, combined with the usage information of the fixed device, the target user's daily routine can be determined.

[0050] Specifically, this embodiment collects the start-up information and first wireless signal of the user's fixed device, the first wireless signal of the user's mobile device, the second wireless signal between the user's fixed device and the user's mobile device, and the corresponding collection time.

[0051] Among them, the start-up information is used to indicate the start-up time, playback time and other usage information of the user's fixed device; the first wireless signal of the user's fixed device is used to indicate the strength of the WiFi signal received by the user's fixed device; the first wireless signal of the user's mobile device is used to indicate the strength of the WiFi signal received by the user's mobile device; the second wireless signal between the user's fixed device and the user's mobile device is used to indicate the strength of the Bluetooth signal between the user's fixed device and the user's mobile device; and the collection time is used to indicate the time when the start-up information and the first wireless signal of the user's fixed device, the first wireless signal of the user's mobile device, and the second wireless signal between the user's fixed device and the user's mobile device are collected.

[0052] Optionally, the collection includes the start-up information and first wireless signal of the user's fixed device, the first wireless signal of the user's mobile device, the second wireless signal between the user's fixed device and the user's mobile device, and the corresponding collection time, including:

[0053] Collect startup and playback information from the user's fixed device as startup information;

[0054] The WiFi signal strength of the user's fixed device is collected as the first wireless signal of the user's fixed device, and the WiFi signal strength of the user's mobile device is collected as the first wireless signal of the user's mobile device.

[0055] The Bluetooth signal strength between the user's fixed device and the user's mobile device is collected as a second wireless signal between the user's fixed device and the user's mobile device.

[0056] The startup information for the user's fixed device includes startup information and playback information, such as startup time and playback time. The WiFi signal strength can be the strength of the WiFi signal received by the user's fixed device or mobile device, and the Bluetooth signal strength can be the strength of the Bluetooth signal between the user's fixed device and / or mobile device.

[0057] Correspondingly, the smaller the device distance between the user's fixed device and / or the user's mobile device, the smaller the difference between the first wireless signal of the user's fixed device and the first wireless signal of the user's mobile device, and the larger the second wireless signal between the user's fixed device and the user's mobile device.

[0058] The steps described above, when the user's fixed device and the target user's mobile device are on the same local area network, involve collecting the user's fixed device's activation information and first wireless signal, the user's mobile device's first wireless signal, the second wireless signal between the user's fixed device and the user's mobile device, and the corresponding collection time. The collection of the first and second wireless signals serves as the basis for determining the target user's mobility information in their place of residence. Combined with the activation information, this provides data support for generating the target user's daily schedule, thereby improving the rationality and accuracy of the generated daily schedule.

[0059] Step S202: Calculate the first wireless signal difference between the first wireless signal of the user's fixed equipment and the first wireless signal of the user's mobile equipment.

[0060] The smaller the distance between the user's fixed device and / or the user's mobile device, the smaller the difference between the first wireless signal of the user's fixed device and the first wireless signal of the user's mobile device. Therefore, the difference between the first wireless signal of the user's fixed device and the first wireless signal of the user's mobile device is calculated to measure the device distance information between the user's fixed device and the user's mobile device.

[0061] The above-described step of calculating the first wireless signal difference between the first wireless signal of the user's fixed device and the first wireless signal of the user's mobile device uses the first wireless signal difference to characterize the device distance information between the user's fixed device and the user's mobile device, thereby improving the efficiency and accuracy of characterizing the device distance information between the user's fixed device and the user's mobile device.

[0062] Step S203: Obtain a preset distance mapping table. Based on the first wireless signal difference, the second wireless signal, and the distance mapping table, obtain the device distance information between the user's fixed device and the user's mobile device. The distance mapping table is used to represent the mapping relationship between the first wireless signal difference, the second wireless signal, and the device distance.

[0063] The distance mapping table is used to represent the mapping relationship between the first wireless signal difference, the second wireless signal, and the device distance. Correspondingly, the smaller the difference between the first wireless signal of the user's fixed device and the first wireless signal of the user's mobile device, the larger the second wireless signal between the user's fixed device and the user's mobile device, and the smaller the device distance between the user's fixed device and the user's mobile device.

[0064] By pre-setting a distance mapping table according to the actual situation, the device distance information between the user's fixed device and the user's mobile device can be obtained based on the first wireless signal difference, the second wireless signal, and the distance mapping table. Since the user's fixed device is a device with a fixed location in the residence, the change in the device distance between the user's fixed device and the user's mobile device can be used to characterize the change in the location of the user's mobile device, which serves as the basis for determining the target user's movement information.

[0065] The steps described above, which involve obtaining a preset distance mapping table and then using the first wireless signal difference, the second wireless signal, and the distance mapping table to obtain device distance information between the user's fixed device and the user's mobile device, map the first wireless signal difference and the second wireless signal to the device distance between the user's fixed device and the user's mobile device based on the preset distance mapping table. This serves as the basis for determining the target user's movement information at their residence, thereby improving the rationality and accuracy of generating the user's schedule.

[0066] Step S204: Send the start-up information, device distance information, and collection time to the server. The server analyzes the start-up information, device distance information, and collection time to obtain the user's schedule corresponding to the target user.

[0067] Among them, the start-up information and device distance information can represent the target user's behavior information and location information. The user's fixed device will send the collected and calculated start-up information, device distance information and collection time to the server to provide the server with the target user's behavior information, so that the server can analyze the start-up information, device distance information and collection time to obtain the user's daily routine list corresponding to the target user.

[0068] The steps described above, which send the start-up information, device distance information, and collection time to the server, use the start-up information and device distance information to characterize the target user's behavior and location information. By sending the start-up information, device distance information, and collection time to the server, the server can analyze and obtain the target user's daily routine list, thereby improving the accuracy of the user's daily routine list.

[0069] This embodiment collects the start-up information and first wireless signal of the user's fixed device, the first wireless signal of the user's mobile device, the second wireless signal between the user's fixed device and the user's mobile device, and the collection time when the user's fixed device and the user's mobile device are on the same local area network. It calculates the first wireless signal difference between the first wireless signal of the user's fixed device and the first wireless signal of the user's mobile device, and obtains the device distance information between the user's fixed device and the user's mobile device based on the first wireless signal difference, the second wireless signal, and a preset distance mapping table. The start-up information, device distance information, and collection time are sent to the server. The start-up information and the signal relationship between the user's fixed device and the user's mobile device are used to characterize the target user's behavior information and location information, thereby improving the accuracy of the user's schedule.

[0070] See Figure 3 This is a flowchart illustrating a user schedule analysis method provided in Embodiment 3 of the present invention. The above-described user schedule analysis method can be applied to... Figure 1 The server-side analysis method for this user's schedule may include the following steps:

[0071] Step S301: Receive the collection time, the start-up information of the user's fixed device, and the device distance information between the user's fixed device and the user's mobile device sent by the target user. Divide the start-up information and device distance information into N groups according to the collection time and a preset time interval.

[0072] Among them, the startup information of the user's fixed device is used to indicate the startup time, playback time and other usage information of the user's fixed device, and the device distance information between the user's fixed device and the target user's mobile device is used to characterize the location change of the user's mobile device.

[0073] The preset time interval can be set according to the actual situation. For example, when using days as the unit, the preset time interval can be set to 3 hours. Then, the start-up information and device distance information can be divided into 8 groups according to the collection time and the preset time interval. Correspondingly, the collection time for the first group of start-up information and device distance information is from 0:00 to 3:00, the collection time for the second group of start-up information and device distance information is from 3:00 to 6:00, and so on, to obtain 8 groups of start-up information and device distance information. This serves as the basis for analyzing the target user's work and rest schedule. By dividing the long-term start-up information and device distance information into multiple short-term start-up information and device distance information, the efficiency and accuracy of user work and rest schedule analysis are improved.

[0074] The steps described above, which involve receiving the collection time, the start-up information of the user's fixed device, and the device distance information between the user's fixed device and the user's mobile device, and then dividing the start-up information and device distance information into N groups based on the collection time and a preset time interval, divide the long-term start-up information and device distance information into multiple short-term start-up information and device distance information, thereby improving the efficiency and accuracy of user schedule analysis.

[0075] Step S302: For any set of start-up information and device distance information, determine the location information of the user's mobile device based on the device distance information, and determine the user's daily routine based on the start-up information and location information.

[0076] Among them, the fixed user device is a device permanently located within the residence, while the mobile user device is a device carried by the target user. Therefore, the change in the distance between the fixed user device and the mobile user device can be used to characterize the change in the location of the mobile user device, and thus characterize the target user's location information within the residence. Different location information can characterize different behavioral information of the target user. This location information can be set according to the actual situation; for example, the location information includes bedrooms, living rooms, studies, kitchens, etc. within the residence.

[0077] Start-up information can be used to characterize the startup and playback information of a user's fixed device, and different start-up information can characterize different behavioral information of the target user. Therefore, this embodiment combines start-up information and location information to characterize the behavioral information of the target user.

[0078] For example, when the smart TV in the living room is turned on and playing music, and the user's mobile device is located in the living room based on the device distance, it can be determined that the target user is watching TV; when the smart TV in the living room is not turned on, and the user's mobile device is located in the living room based on the device distance, it can be determined that the target user is resting; when the smart TV is not turned on, and the user's mobile device is located in the kitchen based on the device distance, it can be determined that the target user is cooking; when the smart TV is not turned on, and the user's mobile device is located in the study based on the device distance, it can be determined that the target user is working or studying; when the smart TV in the living room is not turned on, and the user's mobile device is located in the bedroom based on the device distance, it can be determined that the target user is resting.

[0079] Optionally, determining the location information of the user's mobile device based on device distance information includes:

[0080] Obtain a preset location mapping table, which is used to represent the mapping relationship between device distance information and the location information of the user's mobile device;

[0081] The location information of the user's mobile device is determined based on the device distance information and the location mapping table.

[0082] The location mapping table represents the mapping relationship between device distance information and the location information of the user's mobile device. This mapping relationship can be set according to the actual situation to improve the practicality and rationality of the user's schedule in this embodiment.

[0083] Therefore, firstly, a preset location mapping table is obtained based on the actual situation, and the device distance information obtained from the preset location mapping table is retrieved to determine the location information of the corresponding user's mobile device.

[0084] Optionally, based on the broadcast start information and location information, the target user's daily routine behavior can be determined, including:

[0085] Obtain M preset conditions, and for any preset condition, determine whether the start-up information and location information meet the preset conditions, and obtain the judgment result;

[0086] If the judgment result is that the start-up information and location information meet the preset conditions, then it is determined that the target user will perform the corresponding daily routine behavior.

[0087] If the judgment result is that the start-up information and location information do not meet the preset conditions, it is determined that the target user has not performed the daily routine corresponding to the preset conditions;

[0088] Iterate through M preset conditions and take the daily routine behavior performed by the target user as the user's daily routine behavior.

[0089] Different start-up information and different location information can represent different behavioral information of target users. Therefore, different start-up information and different location information can be correlated with the daily routine of target users. By judging whether the start-up information and location information meet the preset conditions, the daily routine of target users can be determined.

[0090] Specifically, the preset conditions could be: the smart TV is turned on and playing music, the location information is the living room, and the corresponding activity is watching TV; or the smart TV is not turned on, the location information is the living room, and the corresponding activity is resting; or the smart TV is not turned on, the location information is the kitchen, and the corresponding activity is cooking; or the smart TV is not turned on, the location information is the study, and the corresponding activity is working or studying; or the smart TV is not turned on, the location information is the bedroom, and the corresponding activity is sleeping, etc.

[0091] If the start-up information and location information meet the preset conditions, then the target user is determined to perform the corresponding daily routine behavior. If the start-up information and location information do not meet the preset conditions, then the target user is determined not to perform the corresponding daily routine behavior. Then, the M preset conditions are traversed, and the daily routine behavior performed by the target user is taken as the user's daily routine behavior.

[0092] The above steps, which involve determining the location information of the user's mobile device based on the device distance information for any set of start-up information and device distance information, and determining the target user's daily routine behavior based on the start-up information and location information, improve the accuracy of judging user daily routine behavior by combining different start-up information and different location information to characterize different daily routine behaviors of the target user within any time period.

[0093] Step S303: Traverse all start-up information and device distance information to obtain N user activity behaviors, and assemble the N user activity behaviors into a user activity list according to the order of their corresponding collection times.

[0094] Among them, N sets of start-up information and device distance information can correspond to N user daily routines. Then, by combining the N user daily routines in the order of their corresponding collection times, the user daily routine list of the target user can be obtained.

[0095] The above steps, which iterate through all the start-up information and device distance information to obtain N user activity patterns, and then assemble these N user activity patterns into a user activity list according to the order of their corresponding collection times, improve the accuracy of the user activity list by assembling the N user activity patterns and collection times.

[0096] This embodiment receives the collection time, the start-up information of the user's fixed device, and the device distance information between the user's fixed device and the target user's mobile device from the user's fixed device. Based on the collection time and a preset time interval, the start-up information and device distance information are divided into N groups. For any group of start-up information and device distance information, the location information of the user's mobile device is determined based on the device distance information. Based on the start-up information and location information, the target user's daily routine is determined. All start-up information and device distance information are traversed to obtain N user daily routine behaviors. These N user daily routine behaviors are arranged in the order of their corresponding collection times to form a user daily routine list. By combining different start-up information and different location information, different user daily routine behaviors of the target user are characterized, improving the accuracy of user daily routine behavior judgment.

[0097] Corresponding to the user schedule generation method in the above embodiment, Figure 4 A structural block diagram of the user schedule generation device provided in Embodiment 4 of the present invention is given. For ease of explanation, only the parts related to the embodiments of the present invention are shown.

[0098] See Figure 4 The device for generating the user's schedule includes:

[0099] The signal acquisition module 41 is used to acquire the start-up information and first wireless signal of the user fixed device, the first wireless signal of the user mobile device, the second wireless signal between the user fixed device and the user mobile device of the target user, and the corresponding acquisition time when the user fixed device and the user mobile device of the target user are in the same local area network.

[0100] The difference calculation module 42 is used to calculate the first wireless signal difference between the first wireless signal of the user fixed equipment and the first wireless signal of the user mobile equipment;

[0101] The distance mapping module 43 is used to obtain a preset distance mapping table, and obtain the device distance information between the user's fixed device and the user's mobile device based on the first wireless signal difference, the second wireless signal and the distance mapping table. The distance mapping table is used to represent the mapping relationship between the first wireless signal difference, the second wireless signal and the device distance.

[0102] The data sending module 44 is used to send the start-up information, device distance information and collection time to the server. The server is used to analyze the start-up information, device distance information and collection time to obtain the user's schedule corresponding to the target user.

[0103] Optionally, the signal acquisition module 41 mentioned above includes:

[0104] The first signal acquisition submodule is used to collect the startup and playback information of the user's fixed equipment as start-up information;

[0105] The second signal acquisition submodule is used to acquire the WiFi signal strength of the user's fixed device as the first wireless signal of the user's fixed device, and to acquire the WiFi signal strength of the user's mobile device as the first wireless signal of the user's mobile device.

[0106] The third signal acquisition submodule is used to acquire the Bluetooth signal strength between the user's fixed device and the user's mobile device, as a second wireless signal between the user's fixed device and the user's mobile device.

[0107] Corresponding to the user schedule analysis method in the above embodiment, Figure 5 A structural block diagram of the user schedule analysis device provided in Embodiment 5 of the present invention is given. For ease of explanation, only the parts related to the embodiments of the present invention are shown.

[0108] See Figure 5 The analysis device for this user's schedule includes:

[0109] The data acquisition module 51 is used to receive the collection time, the start-up information of the user's fixed device, and the device distance information between the user's fixed device and the user's mobile device sent by the target user. The start-up information and device distance information are divided into N groups according to the collection time and the preset time interval, where N is an integer greater than 0.

[0110] The activity and rest behavior determination module 52 is used to determine the location information of the user's mobile device based on the device distance information for any set of start-up information and device distance information, and to determine the user's activity and rest behavior based on the start-up information and location information.

[0111] The schedule determination module 53 is used to traverse all start-up information and device distance information to obtain N user schedule behaviors, and to assemble the N user schedule behaviors into a user schedule list according to the order of their corresponding collection times.

[0112] Optionally, the above-mentioned daily routine determination module 52 includes:

[0113] The location mapping submodule is used to obtain a preset location mapping table, which represents the mapping relationship between device distance information and the location information of the user's mobile device.

[0114] The location information of the user's mobile device is determined based on the device distance information and the location mapping table.

[0115] Optionally, the above-mentioned daily routine determination module 52 includes:

[0116] The condition judgment submodule is used to obtain M preset conditions, and for any preset condition, to determine whether the start-up information and location information meet the preset conditions, and obtain the judgment result;

[0117] The first result determination submodule is used to determine the target user to perform the corresponding daily routine behavior if the judgment result is that the start-up information and location information meet the preset conditions.

[0118] The second result determination submodule is used to determine that the target user has not performed the corresponding daily routine behavior if the judgment result is that the start-up information and location information do not meet the preset conditions.

[0119] The third result determination submodule is used to traverse M preset conditions and take the target user's daily routine as the user's daily routine.

[0120] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of the present invention. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0121] Figure 6This is a schematic diagram of the structure of a computer device provided in Embodiment Six of the present invention. Figure 6 As shown, the computer device of this embodiment includes: at least one processor ( Figure 6 Only one is shown in the diagram), a memory, and a computer program stored in the memory and executable on at least one processor, which, when executed by the processor, implements the steps in the embodiments of the methods for generating any of the user schedules described above.

[0122] This computer device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that... Figure 6 The examples of computer devices are merely examples and do not constitute a limitation on computer devices. Computer devices may include more or fewer components than shown in the illustration, or combinations of certain components, or different components, such as network interfaces, displays, and input devices.

[0123] The processor referred to can be a CPU, but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0124] Memory includes readable storage media, internal memory, etc., wherein internal memory can be the RAM of a computer device, providing an environment for the operation of the operating system and computer-readable instructions stored in the readable storage media. The readable storage media can be the hard drive of a computer device, or in other embodiments, it can be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, memory can include both internal storage units and external storage devices of a computer device. Memory is used to store the operating system, applications, bootloader, data, and other programs, such as program code for computer programs. Memory can also be used to temporarily store data that has been output or will be output.

[0125] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the functions described above can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this invention. The specific working process of the units and modules in the above device can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the processes in the methods of the above embodiments by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium can include at least: any entity or device capable of carrying computer program code, a recording medium, a computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0126] The present invention can implement all or part of the processes in the methods of the above embodiments, or it can be accomplished by a computer program product. When the computer program product is run on a computer device, the computer device executes the steps in the above method embodiments.

[0127] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0128] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0129] In the embodiments provided by this invention, it should be understood that the disclosed apparatus / computer devices and methods can be implemented in other ways. For example, the apparatus / computer device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0130] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0131] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for generating a user's daily schedule, characterized in that, The generation method includes: When the user's fixed device and the target user's mobile device are on the same local area network, the broadcast start information and first wireless signal of the user's fixed device, the first wireless signal of the user's mobile device, the second wireless signal between the user's fixed device and the user's mobile device, and the corresponding collection time are collected. Calculate the first wireless signal difference between the first wireless signal of the user fixed equipment and the first wireless signal of the user mobile device; A preset distance mapping table is obtained. Based on the first wireless signal difference, the second wireless signal, and the distance mapping table, the device distance information between the user fixed device and the user mobile device is obtained. The distance mapping table is used to characterize the mapping relationship between the first wireless signal difference, the second wireless signal, and the device distance. Send the broadcast start information, the device distance information, and the collection time to the server; The server receives the collection time, the start-up information of the user's fixed device, and the device distance information between the user's fixed device and the user's mobile device from the target user's fixed device. Based on the collection time and a preset time interval, the server divides the start-up information and the device distance information into N groups, where N is an integer greater than 0. For any set of broadcast start information and device distance information, determine the location information of the user's mobile device based on the device distance information, and determine the user's daily routine behavior based on the broadcast start information and the location information; By iterating through all the broadcast information and device distance information, N user daily routines are obtained, and the N user daily routines are arranged into a user daily routine list according to the order of their corresponding collection times.

2. The generation method according to claim 1, characterized in that, The collection of the broadcast activation information and first wireless signal of the user fixed device, the first wireless signal of the user mobile device, the second wireless signal between the user fixed device and the user mobile device, and the corresponding collection time include: The startup and playback information of the user's fixed device are collected as the startup information; The WiFi signal strength of the user's fixed device is collected as the first wireless signal of the user's fixed device, and the WiFi signal strength of the user's mobile device is collected as the first wireless signal of the user's mobile device. The Bluetooth signal strength between the user fixed device and the user mobile device is collected as a second wireless signal between the user fixed device and the user mobile device.

3. The generation method according to claim 1, characterized in that, Determining the location information of the user's mobile device based on the device distance information includes: Obtain a preset location mapping table, which is used to represent the mapping relationship between the device distance information and the location information of the user's mobile device; The location information of the user's mobile device is determined based on the device distance information and the location mapping table.

4. The generation method according to claim 1, characterized in that, The step of determining the target user's daily routine behavior based on the broadcast information and the location information includes: Get M preset conditions, and for any preset condition, determine whether the start-up information and the location information meet the preset conditions to obtain the determination result; If the judgment result is that the broadcast information and the location information meet the preset conditions, then it is determined that the target user performs the daily routine corresponding to the preset conditions; If the judgment result is that the start-up information and the location information do not meet the preset conditions, then it is determined that the target user has not performed the daily routine behavior corresponding to the preset conditions; Iterate through the M preset conditions and take the daily routine behavior performed by the target user as the user's daily routine behavior.

5. A device for generating a user's schedule, characterized in that, The generating apparatus includes: The signal acquisition module is used to acquire, when the user fixed device and the target user's mobile device are on the same local area network, the start-up information and first wireless signal of the user fixed device, the first wireless signal of the user mobile device, the second wireless signal between the user fixed device and the user mobile device, and the corresponding acquisition time. The difference calculation module is used to calculate the first wireless signal difference between the first wireless signal of the user fixed equipment and the first wireless signal of the user mobile device. The distance mapping module is used to obtain a preset distance mapping table, and to obtain the device distance information between the user fixed device and the user mobile device based on the first wireless signal difference, the second wireless signal and the distance mapping table. The distance mapping table is used to characterize the mapping relationship between the first wireless signal difference, the second wireless signal and the device distance. The data sending module is used to send the broadcast start information, the device distance information, and the collection time to the server. The data acquisition module is used to receive the collection time, the start-up information of the user's fixed device, and the device distance information between the user's fixed device and the user's mobile device from the target user's fixed device, and to divide the start-up information and the device distance information into N groups according to the collection time and a preset time interval, where N is an integer greater than 0. The activity and rest behavior determination module is used to determine the location information of the user's mobile device based on the device distance information for any set of the start-up information and the device distance information, and to determine the user's activity and rest behavior of the target user based on the start-up information and the location information. The schedule determination module is used to traverse all the start-up information and the device distance information to obtain N user schedule behaviors, and to assemble the N user schedule behaviors into a user schedule list according to the order of their corresponding collection times.

6. The generating apparatus according to claim 5, characterized in that, The signal acquisition module includes: The first signal acquisition submodule is used to acquire the startup information and playback information of the user's fixed device as the startup information; The second signal acquisition submodule is used to acquire the WiFi signal strength of the user fixed device as the first wireless signal of the user fixed device, and to acquire the WiFi signal strength of the user mobile device as the first wireless signal of the user mobile device. The third signal acquisition submodule is used to acquire the Bluetooth signal strength between the user fixed device and the user mobile device, as a second wireless signal between the user fixed device and the user mobile device.

7. A computer device, characterized in that, The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for generating a user schedule as described in any one of claims 1 to 4.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method for generating a user schedule as described in any one of claims 1 to 4.

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