CN117784625A

CN117784625A - Intelligent prediction method and device for equipment to be controlled

Info

Publication number: CN117784625A
Application number: CN202311813089.9A
Authority: CN
Inventors: 张帆; 陈小平
Original assignee: Foshan Viomi Electrical Technology Co Ltd
Current assignee: Foshan Viomi Electrical Technology Co Ltd
Priority date: 2023-12-26
Filing date: 2023-12-26
Publication date: 2024-03-29

Abstract

The invention relates to the technical field of intelligent home, and discloses an intelligent prediction method and device for equipment to be controlled, wherein the method comprises the following steps: collecting an occurred equipment behavior event corresponding to a target user in a home scene in a target time period; matching the generated equipment behavior event with the determined user behavior sequence of the target user in the target time period to obtain a matching result; and when the matching result shows that the occurred equipment behavior event is not matched with the user behavior sequence, determining the subsequent equipment control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the occurred equipment behavior event. Therefore, when the equipment behavior event is not matched with the user behavior sequence, the current equipment control requirement of the target user can be rapidly predicted, so that the follow-up equipment control efficiency and equipment control convenience are improved based on the rapidly determined equipment control requirement.

Description

Intelligent prediction method and device for equipment to be controlled

Technical Field

The invention relates to the technical field of intelligent home furnishing, in particular to an intelligent prediction method and device for equipment to be controlled.

Background

In the intelligent home scene, different users correspond to different equipment control habits, and intelligent equipment in the intelligent home scene can automatically execute corresponding operations according to the equipment control habits of the users so as to improve the equipment control efficiency and the equipment control convenience.

However, in practical applications, the user can adaptively adjust the device control requirements according to the practical situation, and when the device control requirements are adjusted, how to quickly predict the current device control requirements so as to improve the device control efficiency is important.

Disclosure of Invention

The invention provides an intelligent prediction method and device for equipment to be controlled, which can rapidly predict the current equipment control requirement of a target user, thereby being beneficial to improving the subsequent equipment control efficiency and equipment control convenience based on the rapidly determined equipment control requirement.

In order to solve the technical problem, the first aspect of the present invention discloses an intelligent prediction method for a device to be controlled, which comprises:

collecting an occurred equipment behavior event corresponding to a target user in a home scene in a target time period;

matching the generated equipment behavior event with the determined user behavior sequence of the target user in the target time period to obtain a matching result;

When the matching result indicates that the occurred equipment behavior event is not matched with the user behavior sequence, determining a subsequent equipment control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the occurred equipment behavior event, wherein the subsequent equipment control requirement is used for indicating intelligent household equipment with control requirement of the target user in the target time period, and the intelligent household equipment is equipment to be controlled in the household scene.

In a first aspect of the present invention, the determining, according to the user behavior sequence of the target user in the target time period and the device behavior event that has occurred, a subsequent device control requirement corresponding to the target user includes:

analyzing the equipment behavior requirement of the target user for the equipment behavior event according to the equipment behavior event;

analyzing the user behavior requirements of the target user in the target time period according to the user behavior sequence of the target user in the target time period;

and determining the subsequent equipment control requirement corresponding to the target user according to the equipment behavior requirement and the user behavior requirement.

As an optional implementation manner, in the first aspect of the present invention, the determining, according to the device behavior requirement and the user behavior requirement, a subsequent device control requirement corresponding to the target user includes:

determining a first equipment control requirement of the target user aiming at the equipment behavior requirement according to the equipment behavior requirement;

determining a second equipment control requirement of the target user for the user behavior requirement according to the user behavior requirement;

and carrying out fusion processing on the first equipment control requirement and the second equipment control requirement to obtain the subsequent equipment control requirement corresponding to the target user.

As an alternative embodiment, in the first aspect of the present invention, the method further includes:

after the subsequent equipment control requirement corresponding to the target user is determined, generating equipment control parameters of the intelligent household equipment according to the subsequent equipment control requirement;

and after the determining the subsequent device control requirement corresponding to the target user and before the generating the device control parameter of the smart home device according to the subsequent device control requirement, the method further includes:

Acquiring a prior equipment control requirement corresponding to the target user, wherein the prior equipment control requirement has a corresponding prior time period, and the similarity between a prior user behavior sequence of the target user in the prior time period and the user behavior sequence is greater than or equal to a preset similarity threshold;

and calibrating the subsequent equipment control requirement corresponding to the target user according to the previous equipment control requirement corresponding to the target user, so as to obtain the calibrated subsequent equipment control requirement.

In an optional implementation manner, in a first aspect of the present invention, the matching the generated device behavior event with the determined user behavior sequence of the target user in the target time period to obtain a matching result includes:

calculating the matching degree of the generated equipment behavior event and the determined user behavior sequence of the target user in the target time period;

judging whether the matching degree is smaller than or equal to a preset matching degree threshold value;

when the matching degree is judged to be larger than the matching degree threshold value, determining that the occurred equipment behavior event is matched with the user behavior sequence;

And when the matching degree is smaller than or equal to the matching degree threshold value, determining that the generated equipment behavior event is not matched with the user behavior sequence.

In an optional implementation manner, in a first aspect of the present invention, the calculating a matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target time period includes:

extracting a device behavior feature set corresponding to the generated device behavior event from the generated device behavior event, and extracting a user behavior feature set corresponding to the user behavior sequence from the determined user behavior sequence of the target user in the target time period;

and calculating the matching degree of the generated equipment behavior event and the determined user behavior sequence of the target user in the target time period according to the equipment behavior feature set and the user behavior feature set.

In a first aspect of the present invention, the calculating, according to the device behavior feature set and the user behavior feature set, a matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target time period includes:

According to preset behavior feature categories, grouping a plurality of device behavior features contained in the device behavior feature set and a plurality of user behavior features contained in the user behavior feature set to obtain a plurality of behavior feature groups, wherein the behavior feature categories of all the device behavior features contained in the same behavior feature group are the same as the behavior feature categories of all the contained user behavior features;

for each behavior feature group, calculating initial matching degrees of all equipment behavior features of the behavior feature group and all user behavior features of the behavior feature group, and obtaining initial matching degrees corresponding to the behavior feature group;

and calculating the matching degree of the generated equipment behavior event and the determined user behavior sequence of the target user in the target time period according to the initial matching degree corresponding to all the behavior feature groups.

The second aspect of the invention discloses an intelligent prediction device for equipment to be controlled, which comprises:

the acquisition module is used for acquiring the equipment behavior events which are generated and correspond to the target users in the home scene in the target time period;

the matching module is used for matching the generated equipment behavior event with the determined user behavior sequence of the target user in the target time period to obtain a matching result;

The determining module is configured to determine, when the matching result indicates that the occurred equipment behavior event is not matched with the user behavior sequence, a subsequent equipment control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the occurred equipment behavior event, where the subsequent equipment control requirement is used to indicate an intelligent home equipment with a control requirement of the target user in the target time period, and the intelligent home equipment is to-be-controlled equipment in the home scene.

In a second aspect of the present invention, as an optional implementation manner, the determining module determines, according to the user behavior sequence of the target user in the target time period and the device behavior event that has occurred, a mode of determining a subsequent device control requirement corresponding to the target user specifically includes:

In a second aspect of the present invention, as an optional implementation manner, the determining module determines, according to the device behavior requirement and the user behavior requirement, a subsequent device control requirement corresponding to the target user specifically includes:

As an alternative embodiment, in the second aspect of the present invention, the apparatus further includes:

the generation module is used for generating equipment control parameters of the intelligent home equipment according to the subsequent equipment control requirements after the determination module determines the subsequent equipment control requirements corresponding to the target user;

The acquisition module is further configured to acquire a previous device control requirement corresponding to the target user after the determination module determines the subsequent device control requirement corresponding to the target user and before the generation module generates the device control parameter of the smart home device according to the subsequent device control requirement, where the previous device control requirement has a corresponding previous time period, and a similarity between a previous user behavior sequence of the target user in the previous time period and the user behavior sequence is greater than or equal to a preset similarity threshold;

and, the apparatus further comprises:

and the calibration module is used for calibrating the subsequent equipment control requirement corresponding to the target user according to the previous equipment control requirement corresponding to the target user, so as to obtain the calibrated subsequent equipment control requirement.

In a second aspect of the present invention, as an optional implementation manner, the matching module matches the generated device behavior event with the determined user behavior sequence of the target user in the target time period, so as to obtain a matching result specifically includes:

In a second aspect of the present invention, as an optional implementation manner, the matching module calculates a matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target time period specifically includes:

In a second aspect of the present invention, the matching module calculates, according to the device behavior feature set and the user behavior feature set, a matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target time period, specifically including:

The third aspect of the invention discloses another intelligent prediction device for equipment to be controlled, which comprises:

a memory storing executable program code;

a processor coupled to the memory;

the processor calls the executable program codes stored in the memory to execute the intelligent prediction method of the equipment to be controlled disclosed in the first aspect of the invention.

A fourth aspect of the present invention discloses a computer storage medium storing computer instructions for executing the intelligent prediction method of the device to be controlled disclosed in the first aspect of the present invention when the computer instructions are called.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

in the embodiment of the invention, the generated equipment behavior event corresponding to the target user in the home scene in the target time period is collected; matching the generated equipment behavior event with the determined user behavior sequence of the target user in the target time period to obtain a matching result; when the matching result shows that the equipment behavior event is not matched with the user behavior event, determining a subsequent equipment control requirement corresponding to the target user according to the user behavior event of the target user in the target time period and the equipment behavior event, wherein the subsequent equipment control requirement is used for showing intelligent household equipment with control requirement of the target user in the target time period, and the intelligent household equipment is equipment to be controlled in a household scene. Therefore, the method and the device can be used for rapidly matching the acquired device behavior event corresponding to the target user in the home scene in the target time period with the determined user behavior sequence of the target user in the target time period, determining the subsequent device control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the device behavior event under the condition that the device behavior event is not matched with the user behavior sequence, and rapidly predicting the current device control requirement of the target user, thereby being beneficial to improving the subsequent device control efficiency and the device control convenience based on the rapidly determined device control requirement, improving the control intelligentization degree of the device, and being beneficial to meeting the user requirement and improving the use experience of the user.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic view of a scene to which an intelligent prediction method of a device to be controlled according to an embodiment of the present invention is applied;

FIG. 2 is a schematic flow chart of an intelligent prediction method for a device to be controlled according to an embodiment of the present invention;

FIG. 3 is a schematic flow chart of another intelligent prediction method for a device to be controlled according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of an intelligent prediction apparatus for a device to be controlled according to an embodiment of the present invention;

FIG. 5 is a schematic structural diagram of an intelligent prediction apparatus for another device to be controlled according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of an intelligent prediction apparatus for a device to be controlled according to another embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or article.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The invention discloses an intelligent prediction method and device for equipment to be controlled, which can be used for rapidly matching an acquired equipment behavior event corresponding to a target user in a home scene in a target time period with a determined user behavior sequence of the target user in the target time period, and determining a subsequent equipment control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the equipment behavior event when the acquired equipment behavior event is not matched with the user behavior sequence, so that the current equipment control requirement of the target user can be rapidly predicted, the subsequent equipment control efficiency and the equipment control convenience can be improved based on the rapidly determined equipment control requirement, the control intelligentization degree of equipment can be improved, the user requirement can be met, and the use experience of the user can be improved. The following will describe in detail.

In order to better understand the intelligent prediction method and device for the equipment to be controlled, which are described in the present invention, a description is first given of a home scene to which the intelligent prediction method for the equipment to be controlled is applied, specifically, a scene schematic diagram of the home scene may be shown in fig. 1, fig. 1 is a scene schematic diagram of a home scene to which the adaptive regulation method for implementing equipment based on scene parameters is applied, which is disclosed in the embodiment of the present invention, as shown in fig. 1, where a living room area is taken as an example, and in which intelligent home equipment (such as an intelligent air conditioner and an intelligent sweeper) is placed, and movable target objects (such as users) are in the home scene.

It should be noted that, the schematic view of the scenario shown in fig. 1 is only for showing one scenario to which the intelligent prediction method and apparatus of the device to be controlled are applicable, and is not used for limiting other scenarios to which the intelligent prediction method and apparatus of the device to be controlled are applicable, and the schematic view of the scenario shown in fig. 1 does not limit the shape, size, position, etc. of the smart home device.

Example 1

Referring to fig. 2, fig. 2 is a flow chart of an intelligent prediction method for a device to be controlled according to an embodiment of the present invention. The method for intelligently predicting the device to be controlled described in fig. 2 may be applied to an intelligent predicting device for the device to be controlled, where the device may include a predicting device or a predicting server, where the predicting server may include a cloud server or a local server, and embodiments of the present invention are not limited. As shown in fig. 2, the intelligent prediction method of the device to be controlled may include the following operations:

101. And collecting the generated equipment behavior events corresponding to the target users in the home scene in the target time period.

In the embodiment of the invention, the home scene can be optionally a bedroom scene, a living room scene, a balcony scene and any other indoor or outdoor scene, and the embodiment of the invention is not limited.

In the embodiment of the present invention, optionally, the target time period may be a current time period. The ending time of the current time period may be a current time, and the starting time of the current time period may be a time corresponding to the preset time length of the current time period, which is not limited in the embodiment of the present invention.

In the embodiment of the present invention, the device behavior event that has occurred in the target time period and corresponds to the target user may be a device event generated by the behavior of the target user in the target time period. The behavior of the target user may be that the target user sends the control instruction to the device through voice, or that the target user sends the control instruction to the device through wifi, which is not limited by the embodiment of the invention. Specifically, the device behavior events that have occurred may be collected in a preset behavior event library. Wherein the behavior event library contains a plurality of device behavior events that have occurred. For example, a device behavior Event may be represented by Event, where event= < DeviceID, dateTime, data >, where DeviceID is a device identifier, dateTime is an occurrence time of the device behavior Event, and Data is related description information of the device behavior Event; the user-identified device behavior event may be represented by usersevent, where usersevent= < DeviceID, userID, dateTime, data >, where UserID is the user identification.

102. And matching the generated equipment behavior event with the determined user behavior sequence of the target user in the target time period to obtain a matching result.

In the embodiment of the invention, the user behavior sequence of the target user in the target time period can be one or more user behavior events of the target user in the target time period and event information of each user behavior event. The event information of each user behavior event may include an event occurrence time of the user behavior event, and may further include an event occurrence sequence of the user behavior event. For example, the user behavior event may be represented by usersevent, where usersevent= < DeviceID, userID, dateTime, data >, userID is a user identifier of a target user, at this time, is a device identifier of a device triggered by the target user in the user behavior event, dateTime is an event occurrence time of the user behavior event, and Data is related description information of the user behavior event.

103. And when the matching result shows that the occurred equipment behavior event is not matched with the user behavior sequence, determining the subsequent equipment control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the occurred equipment behavior event.

In the embodiment of the invention, the post-equipment control requirement is used for indicating the intelligent home equipment with the control requirement of the target user in the target time period, and the intelligent home equipment is equipment to be controlled in a home scene. Optionally, the smart home device may include one or more combinations of an intelligent air conditioner, an intelligent sweeper, an intelligent refrigerator, an intelligent clothes airing machine, an intelligent door lock, an intelligent cat eye, an intelligent dryer, an intelligent dehumidifier, and the like, which is not limited in the embodiment of the present invention.

Therefore, the implementation of the intelligent prediction method of the device to be controlled described in fig. 2 can quickly match the collected device behavior event corresponding to the target user in the home scene with the determined user behavior sequence of the target user in the target time period, and determine the subsequent device control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the device behavior event when the device behavior event is not matched with the user behavior sequence, so that the current device control requirement of the target user can be quickly predicted, the subsequent device control efficiency and the device control convenience can be improved based on the quickly determined device control requirement, the control intelligent degree of the device can be improved, the user requirement can be met, and the use experience of the user can be improved.

In an optional embodiment, the matching, in step 102, the sequence of the user behavior of the determined target user in the target time period and the occurred device behavior event to obtain a matching result may include:

when the matching degree is judged to be larger than the matching degree threshold value, determining that the equipment behavior event is matched with the user behavior sequence;

and when the matching degree is less than or equal to the matching degree threshold value, determining that the equipment behavior event is not matched with the user behavior sequence.

In the embodiment of the present invention, the preset matching degree threshold may be 75%, or 80%, or any other set value, which is not limited by the embodiment of the present invention.

Therefore, the optional embodiment can calculate the matching degree of the generated equipment behavior event and the determined user behavior sequence of the target user in the target time period, judge whether the matching degree is smaller than or equal to the preset matching degree threshold, improve the judging accuracy of whether the matching degree is smaller than or equal to the matching degree threshold, determine that the generated equipment behavior event is matched with the user behavior sequence when the matching degree threshold is judged to be larger than, improve the determining speed and the efficiency of the generated equipment behavior event matched with the user behavior sequence, and determine that the generated equipment behavior event is not matched with the user behavior sequence when the matching degree threshold is judged to be smaller than or equal to the matching degree threshold, thereby improving the determining speed and the efficiency of the generated equipment behavior event not matched with the user behavior sequence.

In this optional embodiment, as an optional implementation manner, the calculating the matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target time period may include:

In the embodiment of the present invention, optionally, the set of device behavior features corresponding to the occurred device behavior event may include one or more device behavior features corresponding to the occurred device behavior event. Alternatively, each device behavior feature may be a semantic feature of a device behavior of an occurred device behavior event extracted from related descriptive information of the occurred device behavior event, such as: intelligent door lock recognition (such as recognition of one or more of a face, fingerprint, sound, etc.), intelligent door lock unlocking or intelligent door lock closing, etc.

In the embodiment of the present invention, optionally, the set of user behavior features corresponding to the user behavior sequence may include one or more user behavior features corresponding to the user behavior sequence. Optionally, each user behavior feature may be a semantic feature of the user behavior of any user behavior event in the user behavior sequence, which is extracted from related descriptive information (e.g. the user is used to open the air conditioner and then close the door after opening the door), for example: the user opens the door, the user opens the air conditioner or the user closes the door, etc.

It can be seen that this optional implementation manner can extract a device behavior feature set corresponding to a device behavior event that has occurred from the device behavior event that has occurred, and extract a user behavior feature set corresponding to a user behavior sequence from a determined user behavior sequence of a target user in a target time period, so as to improve extraction accuracy of the behavior feature set (the behavior feature set includes the device behavior feature set/the user behavior feature set), and then calculate, according to the device behavior feature set and the user behavior feature set, a matching degree of the device behavior event that has occurred with the determined user behavior sequence of the target user in the target time period, so as to improve calculation accuracy of the matching degree of the device behavior event that has occurred with the user behavior sequence based on the accurately extracted behavior feature set.

In this optional embodiment, optionally, calculating, according to the device behavior feature set and the user behavior feature set, a matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target time period may include:

grouping a plurality of equipment behavior features contained in the equipment behavior feature set and a plurality of user behavior features contained in the user behavior feature set according to preset behavior feature categories to obtain a plurality of behavior feature groups;

for each behavior feature group, calculating initial matching degrees of all equipment behavior features of the behavior feature group and all user behavior features of the behavior feature group to obtain initial matching degrees corresponding to the behavior feature group;

In the embodiment of the invention, the behavior feature categories of all the behavior features of the equipment contained in the same behavior feature group are the same as the behavior feature categories of all the contained user behavior features. The behavior feature class may be a class of equipment in the equipment control operation (such as a combination of one or more of a door lock class, an air conditioner class, a sweeper class, a clothes airing class, etc.) included in the behavior feature.

In the embodiment of the present invention, optionally, the plurality of device behavior features included in the device behavior feature set may be all the device behavior features included in the device behavior feature set, or may be a number of device behavior features corresponding to all the user behavior features, or may be any other set device behavior features. Optionally, the plurality of user behavior features included in the user behavior feature set may be all user behavior features included in the user behavior feature set, or may be a number of user behavior features corresponding to all device behavior features, or may be any other number of user behavior features that are set, which is not limited by the embodiment of the present invention.

Specifically, the weighted average value calculation can be performed on the initial matching degrees corresponding to all the behavior feature groups, so that the matching degree of the generated equipment behavior event and the determined user behavior sequence of the target user in the target time period is obtained, and the calculation speed and efficiency of the matching degree can be improved.

It can be seen that, in this optional implementation manner, the multiple device behavior features included in the device behavior feature set and the multiple user behavior features included in the user behavior feature set can be grouped according to the preset behavior feature type, the grouping accuracy of the device behavior feature set and the user behavior feature set can be improved based on the preset behavior feature type, then the initial matching degree of all the device behavior features of each behavior feature group obtained after grouping and all the user behavior features of the behavior feature group is calculated, the initial matching degree corresponding to the behavior feature group is obtained, the matching accuracy of each behavior feature group can be improved, the calculating accuracy of the initial matching degree corresponding to each behavior feature group can be improved, and then the matching degree of the user behavior sequence of the device behavior event and the determined target user in the target time period can be calculated according to the initial matching degree corresponding to all the behavior feature groups, so that the calculating accuracy and the reliability of the matching degree can be improved.

In another optional embodiment, before the matching between the occurred device behavior event and the determined user behavior sequence of the target user in the target period of time in step 102, the method may further include:

collecting target information of a target user;

judging whether the initial user information contained in each initial user behavior sequence in all initial user behavior sequence libraries contained in a preset family scene has target information or not, and judging whether the equipment event occurrence time contained in the initial user behavior sequence is in a target time period or not;

when the initial user information contained in the initial user behavior sequence is judged to be free of target information, and/or the equipment event occurrence time contained in the initial user behavior sequence is judged to be not in a target time period, the initial user behavior sequence is eliminated;

when the initial user information contained in the initial user behavior sequence is judged to have target information, and the equipment event occurrence time contained in the initial user behavior sequence is judged to be in a target time period, the initial user behavior sequence is determined to be used as the user behavior sequence of the target user in the target time period.

In the embodiment of the invention, the target information of the target user may be an identity ID code of the target user, or may be facial information of the target user, or may be any other information capable of uniquely identifying the target user, such as fingerprint information or voiceprint information.

It can be seen that, in this optional embodiment, whether the collected target information of the target user exists in the initial user information included in each initial user behavior sequence in all the initial user behavior sequence libraries included in the user behavior sequence library of the preset home scene, and whether the occurrence time of the device event included in the initial user behavior sequence is in the target time period can be determined; the method can improve the judgment accuracy of each initial user behavior sequence through multiple judgment modes, directly exclude the initial user behavior sequence when judging that the initial user information does not have target information and/or the equipment event occurrence time is not in a target time period, and determine the initial user behavior sequence as the user behavior sequence when judging that the initial user information has target information and the equipment event occurrence time is in the target time period, thereby improving the determination accuracy and reliability of the user behavior sequence, and further being beneficial to improving the matching accuracy of the equipment event and the user behavior sequence which occur based on the accurately determined user behavior sequence.

Example two

Referring to fig. 3, fig. 3 is a flow chart of an intelligent prediction method for a device to be controlled according to an embodiment of the present invention. The method for intelligently predicting the device to be controlled described in fig. 3 may be applied to an intelligent predicting device for the device to be controlled, where the device may include a predicting device or a predicting server, where the predicting server may include a cloud server or a local server, and embodiments of the present invention are not limited. As shown in fig. 3, the intelligent prediction method of the device to be controlled may include the following operations:

201. and collecting the generated equipment behavior events corresponding to the target users in the home scene in the target time period.

202. And matching the generated equipment behavior event with the determined user behavior sequence of the target user in the target time period to obtain a matching result.

203. And when the matching result shows that the occurred equipment behavior event is not matched with the user behavior sequence, analyzing equipment behavior requirements of the target user for the occurred equipment behavior event according to the occurred equipment behavior event.

In the embodiment of the invention, the equipment behavior requirement can comprise the behavior required by equipment contained in the occurred equipment behavior event which is confirmed by the target user.

204. And analyzing the user behavior requirements of the target user in the target time period according to the user behavior sequence of the target user in the target time period.

In the embodiment of the invention, the user behavior requirement can comprise the behavior required by the equipment contained in the user behavior sequence which is recognized by the target user in the target time period.

In the embodiment of the present invention, step 204 and step 203 do not occur sequentially, that is, step 204 may occur after step 203, may occur before step 203, or may occur simultaneously with step 203, which is not limited in the embodiment of the present invention.

205. And determining the subsequent equipment control requirement corresponding to the target user according to the equipment behavior requirement and the user behavior requirement.

In the embodiment of the invention, optionally, the equipment behavior requirements and the user behavior requirements can be fused to obtain target behavior requirements, and then the subsequent equipment control requirements corresponding to the target users can be directly determined according to the target behavior requirements; the device control requirements corresponding to the device behavior requirements and the device control requirements corresponding to the user behavior requirements can be determined respectively, and then the two device control requirements are fused to obtain the subsequent device control requirements, so that the selection diversity and flexibility of the determination mode of the subsequent device control requirements can be improved.

Therefore, implementing the intelligent prediction method of the device to be controlled described in fig. 3 can quickly match the collected device behavior event corresponding to the target user in the home scene with the determined user behavior sequence of the target user in the target time period, and determine the subsequent device control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the device behavior event when the device behavior event is not matched with the user behavior sequence, so that the current device control requirement of the target user can be quickly predicted, the subsequent device control efficiency and the device control convenience can be improved based on the quickly determined device control requirement, the control intelligent degree of the device can be improved, the user requirement can be met, and the use experience of the user can be improved. In addition, under the condition that the generated equipment behavior event is not matched with the user behavior sequence, according to the generated equipment behavior event, the equipment behavior requirement of the target user for the generated equipment behavior event is analyzed, the analysis accuracy of the equipment behavior requirement is improved, according to the user behavior sequence of the target user in the target time period, the user behavior requirement of the target user in the target time period is analyzed, the analysis accuracy of the user behavior requirement is improved, and then according to the equipment behavior requirement and the user behavior requirement, the subsequent equipment control requirement corresponding to the target user is determined, and the determination accuracy and reliability of the subsequent equipment control requirement can be improved based on various behavior requirements (the behavior requirements comprise the equipment behavior requirement and the user behavior requirement).

In an alternative embodiment, determining the subsequent device control requirement corresponding to the target user according to the device behavior requirement and the user behavior requirement in step 205 may include:

according to the equipment behavior requirements, determining first equipment control requirements of a target user aiming at the equipment behavior requirements;

determining a second equipment control requirement of the target user aiming at the user behavior requirement according to the user behavior requirement;

In the embodiment of the invention, specifically, a first weight coefficient corresponding to a first equipment control requirement and a second weight coefficient corresponding to a second equipment control requirement may be determined first, then a first product of the first equipment control requirement (for example, the air conditioner is turned up by 2 ℃) and the first weight coefficient corresponding to the first equipment control requirement (for example, 0.4) is calculated, a second product of the second equipment control requirement (for example, the air conditioner is turned up by 3 ℃) and the second weight coefficient corresponding to the second equipment control requirement (for example, 0.6) is calculated, and then a sum of the first product and the second product is calculated to obtain the later equipment control requirement (for example, 2.6 ℃). Optionally, the sum of the first weight coefficient and the second weight coefficient is 1, and the first weight coefficient and the second weight coefficient may be determined according to a preset matching degree selection mechanism (for example, each matching degree corresponds to one first weight coefficient and one second weight coefficient), which is not limited in the embodiment of the present invention.

Therefore, according to the optional embodiment, the first equipment control requirement of the target user aiming at the equipment behavior requirement can be determined according to the equipment behavior requirement, the determination accuracy of the first equipment control requirement is improved, the second equipment control requirement of the target user aiming at the user behavior requirement is determined according to the user behavior requirement, the determination accuracy of the second equipment control requirement is improved, the first equipment control requirement and the second equipment control requirement are subjected to fusion processing, the subsequent equipment control requirement corresponding to the target user is obtained, and the fusion accuracy and reliability of the subsequent equipment control requirement can be improved.

In another alternative embodiment, the method may further comprise:

after the following equipment control requirement corresponding to the target user is determined, equipment control parameters of the intelligent household equipment are generated according to the following equipment control requirement.

In the embodiment of the present invention, optionally, the device control parameter of the smart home device may be an operation parameter for controlling the smart home device. Wherein the device control parameters may include device control signals and/or device control voice commands. The device control signals can be sent to the intelligent household device through wifi, so that the intelligent household device can control operation parameters of the intelligent household device according to the received device control signals. The device control voice parameters can prompt the target user to send the device control voice instruction to the intelligent household device in a voice mode, so that the intelligent household device controls the operation parameters of the intelligent household device according to the received device control voice instruction. Optionally, the control of the scene parameters of the home scene can be achieved by controlling the operation parameters of the smart home device, for example: the control of the air conditioner operation parameters (such as the direction of the air deflector) of the intelligent air conditioner can realize the control of the wind direction in the family scene.

Therefore, the optional embodiment can improve the generation speed and efficiency of the device control parameters of the intelligent home device based on the fast predicted subsequent device control requirement after determining the subsequent device control requirement corresponding to the target user, thereby being beneficial to improving the device control efficiency and the device control convenience of the intelligent home device.

In this optional embodiment, as an optional implementation manner, after determining the subsequent device control requirement corresponding to the target user and before generating the device control parameter of the smart home device according to the subsequent device control requirement, the method may further include:

acquiring a prior equipment control requirement corresponding to a target user;

and calibrating the subsequent equipment control requirement corresponding to the target user according to the preceding equipment control requirement corresponding to the target user, so as to obtain the calibrated subsequent equipment control requirement.

In the embodiment of the invention, the prior equipment control requirement has a corresponding prior time period. The similarity between the previous user behavior sequence and the user behavior sequence of the target user in the previous time period is greater than or equal to a preset similarity threshold. Optionally, the preset similarity threshold may be 85% or 70%, or any other set value, which is not limited by the embodiment of the present invention.

In the embodiment of the invention, specifically, after the calibration is finished and the subsequent equipment control requirement is met, the equipment control parameters of the intelligent household equipment are generated according to the calibrated subsequent equipment control requirement, so that the accuracy and the reliability of the generation of the equipment control parameters can be improved based on the calibrated subsequent equipment control requirement.

Therefore, according to the optional implementation manner, the subsequent equipment control requirements corresponding to the target user can be directly calibrated according to the acquired preceding equipment control requirements corresponding to the target user, and the calibration accuracy and speed of the subsequent equipment control requirements can be improved, so that the accuracy and reliability of the calibrated subsequent equipment control requirements are improved.

Example III

Referring to fig. 4, fig. 4 is a schematic structural diagram of an intelligent prediction apparatus for a device to be controlled according to an embodiment of the present invention. The intelligent prediction apparatus of the device to be controlled described in fig. 4 may include a prediction device or a prediction server, where the prediction server may include a cloud server or a local server, and the embodiment of the present invention is not limited. As shown in fig. 4, the intelligent prediction apparatus of the device to be controlled may include:

The collection module 301 is configured to collect, in a target period of time, an occurred device behavior event corresponding to a target user in a home scene.

And the matching module 302 is configured to match the generated device behavior event with the determined user behavior sequence of the target user in the target time period, so as to obtain a matching result.

The determining module 303 is configured to determine, when the matching result indicates that the device behavior event does not match the user behavior event, a subsequent device control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the device behavior event that has occurred, where the subsequent device control requirement is used to indicate an intelligent home device that has a control requirement for the target user in the target time period, where the intelligent home device is a device to be controlled in a home scene.

Therefore, the intelligent prediction apparatus for the device to be controlled described in fig. 4 can be implemented to quickly match the collected device behavior event corresponding to the target user in the home scene with the determined user behavior sequence of the target user in the target time period, and determine the subsequent device control requirement corresponding to the target user according to the user behavior sequence of the target user in the target time period and the device behavior event when the device behavior event is not matched with the user behavior sequence, so that the current device control requirement of the target user can be quickly predicted, thereby being beneficial to improving the subsequent device control efficiency and the device control convenience based on the quickly determined device control requirement, improving the control intelligent degree of the device, being beneficial to meeting the user requirement and improving the use experience of the user.

In an alternative embodiment, the determining module 303 may specifically determine, according to the user behavior sequence of the target user in the target period and the device behavior event that has occurred, a manner of determining the subsequent device control requirement corresponding to the target user, where the manner may include:

according to the equipment behavior event, analyzing equipment behavior requirements of a target user aiming at the equipment behavior event;

according to a user behavior sequence of a target user in a target time period, analyzing user behavior requirements of the target user in the target time period;

Therefore, in the optional embodiment, under the condition that the generated equipment behavior event is not matched with the user behavior sequence, according to the generated equipment behavior event, the equipment behavior requirement of the target user for the generated equipment behavior event is analyzed, the analysis accuracy of the equipment behavior requirement is improved, according to the user behavior sequence of the target user in the target time period, the user behavior requirement of the target user in the target time period is analyzed, the analysis accuracy of the user behavior requirement is improved, and then according to the equipment behavior requirement and the user behavior requirement, the subsequent equipment control requirement corresponding to the target user is determined, and the determination accuracy and reliability of the subsequent equipment control requirement can be improved based on various behavior requirements (the behavior requirements comprise the equipment behavior requirement and the user behavior requirement).

In this optional embodiment, as an optional implementation manner, the determining module may specifically determine, according to the device behavior requirement and the user behavior requirement, a mode of determining a subsequent device control requirement corresponding to the target user, where the subsequent device control requirement includes:

Therefore, according to the optional implementation manner, the first equipment control requirement of the target user aiming at the equipment behavior requirement can be determined according to the equipment behavior requirement, the determination accuracy of the first equipment control requirement is improved, the second equipment control requirement of the target user aiming at the user behavior requirement is determined according to the user behavior requirement, the determination accuracy of the second equipment control requirement is improved, the first equipment control requirement and the second equipment control requirement are subjected to fusion processing, the subsequent equipment control requirement corresponding to the target user is obtained, and the fusion accuracy and reliability of the subsequent equipment control requirement can be improved.

In another alternative embodiment, as shown in fig. 5, the apparatus may further include:

the generating module 304 is configured to generate device control parameters of the smart home device according to the subsequent device control requirements after the determining module 303 determines the subsequent device control requirements corresponding to the target user.

In this optional embodiment, as an optional implementation manner, the collecting module 301 is further configured to collect, after the determining module 303 determines the subsequent device control requirement corresponding to the target user and before the generating module 304 generates the device control parameter of the smart home device according to the subsequent device control requirement, a previous device control requirement corresponding to the target user, where the previous device control requirement exists in a corresponding previous time period, and a similarity between a previous user behavior sequence and a user behavior sequence of the target user in the previous time period is greater than or equal to a preset similarity threshold. And, as shown in fig. 5, the apparatus may further include:

The calibration module 305 is configured to calibrate the subsequent device control requirement corresponding to the target user according to the previous device control requirement corresponding to the target user, so as to obtain the calibrated subsequent device control requirement.

In yet another alternative embodiment, the matching module 302 matches the occurred device behavior event with the determined user behavior sequence of the target user in the target time period, and the manner of obtaining the matching result may specifically include:

In this optional embodiment, as an optional implementation manner, the matching module 302 may specifically calculate the matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target period of time, where the method includes:

In this optional embodiment, optionally, the method for calculating, by the matching module, the matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target time period according to the device behavior feature set and the user behavior feature set may specifically include:

Grouping a plurality of device behavior features contained in a device behavior feature set and a plurality of user behavior features contained in a user behavior feature set according to preset behavior feature categories to obtain a plurality of behavior feature groups, wherein the behavior feature categories of all the device behavior features contained in the same behavior feature group are identical to the behavior feature categories of all the contained user behavior features;

Example IV

Referring to fig. 6, fig. 6 is a schematic structural diagram of an intelligent prediction apparatus for a device to be controlled according to an embodiment of the present invention. As shown in fig. 6, the intelligent prediction apparatus of the device to be controlled may include:

a memory 401 storing executable program codes;

a processor 402 coupled with the memory 401;

the processor 402 invokes executable program codes stored in the memory 401 to execute steps in the intelligent prediction method of the device to be controlled described in the first or second embodiment of the present invention.

Example five

The embodiment of the invention discloses a computer storage medium which stores computer instructions for executing the steps in the intelligent prediction method of the equipment to be controlled described in the first embodiment or the second embodiment of the invention when the computer instructions are called.

Example six

An embodiment of the present invention discloses a computer program product comprising a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute steps in the intelligent prediction method of a device to be controlled described in the first or second embodiment.

The apparatus embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.

Finally, it should be noted that: the embodiment of the invention discloses an intelligent prediction method and device for equipment to be controlled, which are disclosed by the embodiment of the invention only as the preferred embodiment of the invention, and are only used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims

1. An intelligent prediction method for equipment to be controlled, characterized in that the method comprises the following steps:

2. The method for intelligently predicting a device to be controlled according to claim 1, wherein the determining, according to the user behavior sequence of the target user in the target time period and the device behavior event that has occurred, a subsequent device control requirement corresponding to the target user includes:

3. The method for intelligently predicting a device to be controlled according to claim 2, wherein determining the subsequent device control requirement corresponding to the target user according to the device behavior requirement and the user behavior requirement comprises:

4. A method of intelligent prediction of a device to be controlled according to any one of claims 1-3, characterized in that the method further comprises:

5. The method for intelligently predicting a device to be controlled according to any one of claims 1 to 3, wherein the matching the occurred device behavior event with the determined user behavior sequence of the target user in the target time period to obtain a matching result includes:

6. The method for intelligent prediction of a device to be controlled according to claim 5, wherein the calculating the matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target time period includes:

7. The method for intelligently predicting a device to be controlled according to claim 6, wherein calculating the matching degree between the occurred device behavior event and the determined user behavior sequence of the target user in the target time period according to the device behavior feature set and the user behavior feature set comprises:

8. An intelligent prediction apparatus for a device to be controlled, the apparatus comprising:

9. An intelligent prediction apparatus for a device to be controlled, the apparatus comprising:

a memory storing executable program code;

a processor coupled to the memory;

the processor invokes the executable program code stored in the memory to perform the intelligent predictive method of a device to be controlled as claimed in any one of claims 1 to 7.

10. A computer storage medium storing computer instructions which, when invoked, are adapted to perform the intelligent predictive method of a device to be controlled according to any one of claims 1-7.